Triple
T4031682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brigadoon (choreography) |
E83726
|
entity |
| Predicate | firstProducedFor |
P53547
|
FINISHED |
| Object | original Broadway production of Brigadoon |
—
|
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: original Broadway production of Brigadoon | Statement: [Brigadoon (choreography), firstProducedFor, original Broadway production of Brigadoon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstProducedFor Context triple: [Brigadoon (choreography), firstProducedFor, original Broadway production of Brigadoon]
-
A.
firstProducedAt
Indicates the location or context where something was originally created, manufactured, or brought into existence for the first time.
-
B.
firstProductionYear
Indicates the year in which something (such as a product, work, or item) was first produced.
-
C.
firstUsedOn
Indicates the date, time, or context in which something was initially applied, activated, or put into use on a particular object or entity.
-
D.
modelProduced
Indicates that a particular model has generated or produced a specified output, result, or artifact.
-
E.
producedOn
Indicates that something was created, manufactured, or brought into existence at a specific date or time.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb0dbb8481909ff2ee49dadcd1dc |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:36 p.m.