Triple
T10290570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opéra Bastille |
E241350
|
entity |
| Predicate | mainAuditoriumCapacity |
P72212
|
FINISHED |
| Object | about 2700 |
—
|
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 2700 | Statement: [Opéra Bastille, mainAuditoriumCapacity, about 2700]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAuditoriumCapacity Context triple: [Opéra Bastille, mainAuditoriumCapacity, about 2700]
-
A.
audienceCapacityType
Indicates the classification or type of capacity used to describe how many audience members a venue or event space can accommodate.
-
B.
mainHallCapacity
chosen
Indicates the maximum number of people that the main hall can accommodate at one time.
-
C.
hasAuditorium
Indicates that one entity possesses or includes an auditorium as part of its facilities.
-
D.
shapeOfOriginalAuditorium
Indicates the geometric form or layout that characterized the auditorium in its original design or construction.
-
E.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:41 a.m.