Triple
T24089140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doonesbury |
E596739
|
entity |
| Predicate | broadwayPerformancesCount |
P25301
|
FINISHED |
| Object | 104 |
—
|
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: 104 | Statement: [Doonesbury, broadwayPerformancesCount, 104]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: broadwayPerformancesCount Context triple: [Doonesbury, broadwayPerformancesCount, 104]
-
A.
numberOfBroadwayPerformances
chosen
Indicates the total count of times a production or performance has been staged on Broadway.
-
B.
hasBroadwayProduction
Indicates that a work or show has been produced and staged in a Broadway theater.
-
C.
appearedInBroadwayProduction
Indicates that an entity participated as part of a Broadway stage production of another work or show.
-
D.
numberOfWestEndPerformances
Indicates the total count of performances of a production that took place in London’s West End.
-
E.
hasBroadwayExperience
Indicates that an entity has participated in or worked on a Broadway production in some professional capacity.
- 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_69e288c4638c81909bacc28a1e3d436b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dc2c58448190a6e1cf25ae228a2e |
completed | April 29, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:48 p.m.