Triple
T17401917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlington, Texas |
E423109
|
entity |
| Predicate | sportsFacilityType |
P25287
|
FINISHED |
| Object | NFL stadium |
—
|
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: NFL stadium | Statement: [Arlington, Texas, sportsFacilityType, NFL stadium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsFacilityType Context triple: [Arlington, Texas, sportsFacilityType, NFL stadium]
-
A.
sportsFacility
Indicates that one entity is a sports facility where sports or physical activities can take place for the other entity.
-
B.
sportsVenueFor
Indicates that a venue is used as the location or facility where a particular sport or sporting event takes place.
-
C.
OlympicVenueType
Indicates the specific type or classification of a venue used for Olympic events.
-
D.
hasSportsVenueType
chosen
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
E.
gameVenue
Indicates the location or facility where a game or match is held.
- 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_69d889d710288190bf0f4762801fefae |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43b046ad88190a95bbeda4e602514 |
completed | April 19, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b02e6cc88190986e85e64ce9383e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.