Triple
T12927570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newborn |
E309282
|
entity |
| Predicate | emotionTraits |
P87208
|
FINISHED |
| Object | displays disturbingly human-like emotions |
—
|
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: displays disturbingly human-like emotions | Statement: [Newborn, emotionTraits, displays disturbingly human-like emotions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionTraits Context triple: [Newborn, emotionTraits, displays disturbingly human-like emotions]
-
A.
emotionalTrait
chosen
Indicates that an entity possesses a particular emotional characteristic, disposition, or affective quality.
-
B.
emotionChip
Indicates that an entity possesses or is equipped with an emotion chip that enables emotional processing or simulation.
-
C.
emotionState
Indicates the emotional condition or feeling that an entity is currently experiencing.
-
D.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
E.
emotionDomain
Indicates the general emotional category or type to which a specific emotion belongs (e.g., grouping emotions into broader domains like joy, anger, or fear).
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971ec72a48190aceef10630603d2c |
completed | April 10, 2026, 9:55 p.m. |
| PD | Predicate disambiguation | batch_69d96fab4d0881909a7a4d66bab9aa85 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.