Triple
T2367416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Latino |
E46013
|
entity |
| Predicate | hasGrandstands |
P32066
|
FINISHED |
| Object | concrete stands |
—
|
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: concrete stands | Statement: [El Latino, hasGrandstands, concrete stands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrandstands Context triple: [El Latino, hasGrandstands, concrete stands]
-
A.
stadiumFeature
chosen
Indicates that a stadium possesses or includes a particular feature, characteristic, or facility.
-
B.
stadium
Indicates that an entity is a sports or event venue where games, competitions, or large gatherings take place.
-
C.
containsStadium
Indicates that a location or area includes a stadium within its boundaries or premises.
-
D.
notableStadium
Indicates that an entity is a stadium that is particularly prominent, famous, or significant in some notable way.
-
E.
mainStadium
Indicates that a particular stadium serves as the primary or home stadium associated with an entity (such as a team, club, or organization).
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc74b6bdc8190a12b2bcaa2dd7616 |
completed | March 7, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69abc59b88348190a2d6c08f69974117 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:56 p.m.