Triple
T27627449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southwest Classic |
E696244
|
entity |
| Predicate | typicalVenueState |
P201257
|
FINISHED |
| Object | Texas |
—
|
NE NERFINISHED |
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: Texas | Statement: [Southwest Classic, typicalVenueState, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVenueState Context triple: [Southwest Classic, typicalVenueState, Texas]
-
A.
homeVenueState
Indicates the state in which an entity’s home venue is located.
-
B.
venueState
Indicates the state or region in which a given venue is located.
-
C.
typicalVenueSetting
Indicates the usual or characteristic type of venue or setting in which an event, activity, or interaction typically takes place.
-
D.
typicalVenues
Indicates that the specified locations are common or standard places where the associated activity, event, or entity usually occurs or is hosted.
-
E.
formerTypicalVenue
Indicates that a location was once the usual or primary venue for an entity’s activities or events, but no longer serves in that typical role.
- 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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69ffe23081408190a121d901dbce1403 |
completed | May 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69ffe18aed348190912a5996b2da728b |
completed | May 10, 2026, 1:38 a.m. |
| PDg | Predicate description generation | batch_69ffe22f453c81909867ee2d2047636f |
completed | May 10, 2026, 1:41 a.m. |
Created at: April 27, 2026, 2:18 p.m.