Triple
T23044367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lone Star Park Handicap |
E573833
|
entity |
| Predicate | hasVenueCounty |
P103129
|
FINISHED |
| Object | Dallas County |
—
|
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: Dallas County | Statement: [Lone Star Park Handicap, hasVenueCounty, Dallas County]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVenueCounty Context triple: [Lone Star Park Handicap, hasVenueCounty, Dallas County]
-
A.
primaryVenueCounty
Indicates the county that serves as the main or principal venue associated with an event, organization, or activity.
-
B.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
C.
hasVenueFor
Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
-
D.
hasVenueContext
Indicates that an entity is associated with a particular venue or setting that provides contextual information about where it occurs or is situated.
-
E.
isVenueWithin
chosen
Indicates that one venue is geographically located inside the boundaries or area of another place or region.
- 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_69e245b9c11481909d06c872214d21af |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18517083c8190a0850da5440e0a73 |
completed | April 29, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69ef89d5f71881908b9f9d0c8aab278c |
completed | April 27, 2026, 4:07 p.m. |
Created at: April 17, 2026, 3:54 p.m.