Triple
T4105697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quartier des Spectacles |
E88445
|
entity |
| Predicate | numberOfPerformanceHalls |
P2490
|
FINISHED |
| Object | about 30 performance halls |
—
|
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: about 30 performance halls | Statement: [Quartier des Spectacles, numberOfPerformanceHalls, about 30 performance halls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPerformanceHalls Context triple: [Quartier des Spectacles, numberOfPerformanceHalls, about 30 performance halls]
-
A.
numberOfHalls
chosen
Indicates the quantity of halls associated with a given entity or location.
-
B.
hasAuditorium
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
C.
numberOfVenues
Indicates the total count of venues associated with a given entity or context.
-
D.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
-
E.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03d7240c8190a64dcbc669772808 |
completed | March 9, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69af0183eb84819087d7184de28f5514 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:40 p.m.