Triple
T3506796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Quarter |
E74094
|
entity |
| Predicate | hasMajorVenueCapacityOver |
P13342
|
FINISHED |
| Object | 10000 spectators |
—
|
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: 10000 spectators | Statement: [Rose Quarter, hasMajorVenueCapacityOver, 10000 spectators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorVenueCapacityOver Context triple: [Rose Quarter, hasMajorVenueCapacityOver, 10000 spectators]
-
A.
hasMajorVenue
chosen
Indicates that an entity is associated with a primary or principal venue where its main activities or events take place.
-
B.
stadiumCapacityApprox
Indicates an approximate number of people that a stadium can accommodate.
-
C.
homeArenaCapacity
Indicates the maximum number of spectators that can be accommodated in an entity’s home arena.
-
D.
hasProfessionalSportsVenue
Indicates that one entity possesses or hosts a venue specifically used for professional sports events.
-
E.
stadiumCapacityContext
Indicates the seating capacity of a stadium as it applies within a specific contextual scope (such as time, event, or configuration).
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbf52bd8819085a2ac5f48cc5c68 |
completed | March 8, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.