Triple
T24442069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loudon, New Hampshire |
E616291
|
entity |
| Predicate | hasEventVenueType |
P25287
|
FINISHED |
| Object | NASCAR race track |
—
|
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: NASCAR race track | Statement: [Loudon, New Hampshire, hasEventVenueType, NASCAR race track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEventVenueType Context triple: [Loudon, New Hampshire, hasEventVenueType, NASCAR race track]
-
A.
hasVenueComponentType
Indicates that a venue is associated with a specific type of component or functional part it contains or comprises.
-
B.
hasVenueFor
Indicates that one entity provides or serves as the location or setting where an event, activity, or function takes place for another entity.
-
C.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
D.
hasSportsVenueType
chosen
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
E.
hasExhibitionVenueType
Indicates the type or category of venue where an exhibition is held or presented.
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2985129cc8190b5c99747d2dbcac8 |
completed | April 29, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
Created at: April 18, 2026, 2:17 a.m.