feat(annotate): first-person memory narrative + shorter speech prompts

- module_1_memory: rewrite as an explicit first-person, past-tense
  narrative ("I picked up...", "I opened...") matching the MEM
  (Torne 2026) running-memory style, instead of "one or two short
  sentences" with no person/tense guidance.
- module_1_task_rephrasings: bias rephrasings toward short imperative.
- module_2_initial_speech: prefer very short robot acknowledgements.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Pepijn
2026-05-19 14:17:30 +02:00
parent ce47075d6b
commit 134a707c7a
3 changed files with 24 additions and 11 deletions
@@ -8,18 +8,29 @@ task execution. Specific object attributes (colors, precise quantities of
each item) get discarded when their details won't affect subsequent
actions. Functional outcomes (where items went, how many) are preserved."
Concrete example from MEM:
Before: "I put a light green bowl, a dark blue bowl and a bright yellow
bowl into the top right cabinet"
After: "I placed three bowls in the top right cabinet"
Episode task: "{episode_task}"
Previous memory: {prior_memory}
Just-completed subtask: "{completed_subtask}"
Remaining subtasks (for relevance judgement only): {remaining_subtasks}
Update the memory. Drop irrelevant detail. Compress completed steps.
Keep WHAT happened, drop HOW. Shorter is better.
Write the memory as a short FIRST-PERSON, PAST-TENSE narrative of what the
robot has accomplished so far — the running story it would tell itself.
Authoring rules:
- First person, past tense. Every sentence starts with "I": "I picked
up...", "I opened...", "I moved to...".
- One or two short sentences. Extend the previous memory with the
just-completed subtask; do not rewrite it from scratch.
- Keep WHAT happened (functional outcomes — where items went, how many),
drop HOW (grasp details, motions).
- Compress completed steps and drop object attributes (colors, exact
counts) once they no longer affect the remaining subtasks.
Example (MEM, Torne 2026):
Before: "I prepared the pot and got the potatoes, milk, and butter. I
moved to the drawer."
After: "I prepared the pot and got the ingredients. I opened the
drawer with the masher."
Output strictly valid JSON:
{{ "memory": "<one or two short sentences>" }}
{{ "memory": "<one or two short first-person past-tense sentences>" }}
@@ -9,7 +9,7 @@ Original task:
Generate exactly {n} alternative phrasings of the same task. Vary:
- formality (casual / polite / curt)
- verbosity (short imperative vs longer polite request)
- verbosity (mostly short imperative; occasional polite request)
- word choice (synonyms, different verbs)
- sentence structure (imperative / question / suggestion)
@@ -17,7 +17,7 @@ Hard rules:
- Each phrasing MUST preserve the exact meaning of the original task.
Do not change which object is involved, the destination, or the
action. Do not add extra steps. Do not invent new objects.
- Each phrasing must be a single short sentence, plain prose, no
- Each phrasing must be a short phrase or sentence, plain prose, no
markdown, no quotes, no list numbers.
- Phrasings must be distinct — no near-duplicates.
- Output exactly {n} entries.
@@ -1,10 +1,12 @@
The user just asked the robot: "{episode_task}".
Generate a short verbal acknowledgement the robot would speak back before
beginning the task. Style: confident, friendly, single short sentence.
beginning the task. Style: compact, confident, friendly.
Examples (Hi Robot, Shi 2025): "Sure, I won't put cheese on it.",
"OK, starting with the sponge.", "Got it.".
Prefer very short replies: "Got it.", "On it.", "OK."
Output strictly valid JSON:
{{ "text": "<the spoken acknowledgement>" }}