Triple
T14036157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olympic Indoor Hall |
E337715
|
entity |
| Predicate | capacityGymnastics |
P112577
|
FINISHED |
| Object | approximately 17000 |
—
|
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: approximately 17000 | Statement: [Olympic Indoor Hall, capacityGymnastics, approximately 17000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capacityGymnastics Context triple: [Olympic Indoor Hall, capacityGymnastics, approximately 17000]
-
A.
capacityForBasketball
Indicates the ability or suitability of an entity to play or perform well in basketball.
-
B.
capacityDuringOlympics
Indicates the seating or usage capacity of a venue, facility, or service specifically during the Olympic Games period.
-
C.
gymnasticsStar
Indicates that one entity is recognized as an outstanding or star performer in gymnastics.
-
D.
standingCapacity
Indicates the maximum number of people that are allowed or able to stand in a given space or vehicle.
-
E.
capacityCategory
Indicates the classification of something based on the amount or volume it can hold, handle, or accommodate.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de30e312148190a6be0a3258364e6e |
completed | April 14, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.