Triple
T29002662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Red-Haired Girl |
E736344
|
entity |
| Predicate | emotionalEffectOnCharlieBrown |
P52747
|
FINISHED |
| Object | nervousness |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: nervousness | Statement: [Little Red-Haired Girl, emotionalEffectOnCharlieBrown, nervousness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalEffectOnCharlieBrown Context triple: [Little Red-Haired Girl, emotionalEffectOnCharlieBrown, nervousness]
-
A.
emotionEffect
chosen
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
B.
emotionChip
Indicates that an entity possesses or is equipped with an emotion chip that enables emotional processing or simulation.
-
C.
intendedEmotion
Indicates the emotion that an action, expression, or communication is meant to evoke in its target, regardless of the actual emotion experienced.
-
D.
emotionalChallenge
Indicates a situation where one entity causes or experiences significant emotional difficulty or stress in relation to another entity or circumstance.
-
E.
comfortsCharacter
Indicates that one character provides emotional support or consolation to another character.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fbd59d0819095a6bfb40c7c96d5 |
completed | May 2, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69f659d297cc8190b2b962ba30a1edb3 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:35 a.m.