Triple
T8580872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sally Hayes |
E203172
|
entity |
| Predicate | sceneInvolvement |
P17462
|
FINISHED |
| Object | theater date scene |
—
|
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: theater date scene | Statement: [Sally Hayes, sceneInvolvement, theater date scene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sceneInvolvement Context triple: [Sally Hayes, sceneInvolvement, theater date scene]
-
A.
plotInvolvement
chosen
Indicates that an entity participates in, contributes to, or is affected by the events or storyline of a narrative work.
-
B.
hasBeenInvolvedIn
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
C.
typeOfInvolvement
Indicates the specific role, capacity, or manner in which one entity is involved with or participates in another entity or activity.
-
D.
constantInvolved
Indicates that a constant participates in or is directly involved in the specified relation, operation, or context.
-
E.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbeb1a026c819089183f542eeb7837 |
completed | March 31, 2026, 3:41 p.m. |
| PD | Predicate disambiguation | batch_69cbd11b13108190b07f8f161425a585 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:22 p.m.