Triple
T7049659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondine |
E163731
|
entity |
| Predicate | broadwayAdaptationLanguage |
P74741
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Ondine, broadwayAdaptationLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: broadwayAdaptationLanguage Context triple: [Ondine, broadwayAdaptationLanguage, English]
-
A.
broadwayOriginalLanguage
Indicates the original language in which a Broadway production was first written or performed.
-
B.
hasBroadwayTitle
Indicates that an entity is associated with a specific title used for its Broadway production or representation.
-
C.
hasBroadwayProduction
Indicates that a work or show has been produced and staged in a Broadway theater.
-
D.
appearedInBroadwayProduction
Indicates that an entity participated as part of a Broadway stage production of another work or show.
-
E.
areSpokenIn
Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
- 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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
| PDg | Predicate description generation | batch_69c6e4a15b088190bee9a23e94aaac53 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:37 p.m.