Triple
T38527102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady in the Dark universe |
E923256
|
entity |
| Predicate | hasOriginalProductionVenue |
P43663
|
FINISHED |
| Object |
Broadway
Broadway is New York City's famed theater district, renowned as the premier center for large-scale professional stage productions and musicals.
|
E16252
|
NE FINISHED |
How this triple was built (3 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: Broadway | Statement: [Lady in the Dark universe, hasOriginalProductionVenue, Broadway]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Broadway Triple: [Lady in the Dark universe, hasOriginalProductionVenue, Broadway]
Generated description
Broadway is New York City's famed theater district, renowned as the premier center for large-scale professional stage productions and musicals.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalProductionVenue Context triple: [Lady in the Dark universe, hasOriginalProductionVenue, Broadway]
-
A.
hasOriginalProducer
Indicates that an entity was initially created, manufactured, or produced by a specific producer or organization.
-
B.
originalPerformanceVenue
chosen
Indicates the venue where a performance was first originally presented or premiered.
-
C.
originallyProducedAs
Indicates that one entity was first created, released, or manufactured in the form of another specified entity or format.
-
D.
originallyProducedIn
Indicates that something was first created, manufactured, or brought into existence in a particular place or location.
-
E.
locationOfOriginals
Indicates the place where the original versions or source items of something are kept or found.
- F. None of above.
Provenance (6 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_69f76ea8f6348190a5c03fb6292bbee3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff49016dcc8190a8a43868c728b4f1 |
completed | May 9, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41e01fded481908e74ff245d81377c |
completed | June 29, 2026, 3:01 a.m. |
| NEDg | Description generation | batch_6a41e28c66a48190ba743af96d4efa0d |
completed | June 29, 2026, 3:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41e3145eec81909453851382cd43f2 |
completed | June 29, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69ff4891924c8190b5be340e2520e012 |
completed | May 9, 2026, 2:45 p.m. |
Created at: May 3, 2026, 4:32 p.m.