Triple
T996643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | People Will Say We're in Love |
E21509
|
entity |
| Predicate | theatricalContext |
P21697
|
FINISHED |
| Object | romantic duet between Curly and Laurey |
—
|
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: romantic duet between Curly and Laurey | Statement: [People Will Say We're in Love, theatricalContext, romantic duet between Curly and Laurey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theatricalContext Context triple: [People Will Say We're in Love, theatricalContext, romantic duet between Curly and Laurey]
-
A.
theatricalSetting
Indicates the spatial or contextual environment in which a theatrical performance or dramatic action takes place.
-
B.
theatre
Indicates that an entity is a theater or is associated with theatrical performances or activities.
-
C.
theater
Indicates that an entity is a theater or is functioning in the role of a theater (a venue where performances or films are shown).
-
D.
relatedTheater
Indicates a relationship where one entity is associated with, connected to, or relevant in the context of a particular theater or theatrical venue.
-
E.
theatreType
Indicates the specific category or kind of theatre associated with an entity, such as its format, style, or operational model.
- F. None of above. chosen
Provenance (4 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4df6dcc819084a7c0a50637a2c2 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b30efd2c8190b780a6dee086d0aa |
completed | March 1, 2026, 9:43 p.m. |
Created at: March 1, 2026, 7:41 p.m.