Triple
T16601833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTSA Roadrunners football team |
E403346
|
entity |
| Predicate | homeGameCityPopulationCategory |
P123490
|
FINISHED |
| Object | large city |
—
|
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: large city | Statement: [UTSA Roadrunners football team, homeGameCityPopulationCategory, large city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeGameCityPopulationCategory Context triple: [UTSA Roadrunners football team, homeGameCityPopulationCategory, large city]
-
A.
game5City
Indicates that a particular game or sporting event took place in, or is associated with, a specific city.
-
B.
homeCityPopulationRegion
Indicates that the population of a home city falls within or is associated with a specified geographic region.
-
C.
cityOfGames
Indicates that a location is recognized as a major center or hub for games, gaming activities, or the games industry.
-
D.
game2City
Indicates a relationship where a game is associated with, takes place in, or is otherwise linked to a particular city.
-
E.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35d770a048190be42180b03efba0b |
completed | April 18, 2026, 10:31 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.