Triple
T18381485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Leahy Field |
E446457
|
entity |
| Predicate | hasVenueComponentType |
P130916
|
FINISHED |
| Object | field |
—
|
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: field | Statement: [Frank Leahy Field, hasVenueComponentType, field]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVenueComponentType Context triple: [Frank Leahy Field, hasVenueComponentType, field]
-
A.
hasVenueIn
Indicates that an event, activity, or occurrence takes place at a specific venue located within a particular geographic area or location.
-
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.
hasVenueFunction
Indicates that a venue serves a particular function or role (such as hosting events, performances, or specific activities).
-
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.
hasPrincipalVenue
Indicates that an entity has a primary or main venue where its activities, events, or operations predominantly take place.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5179b60f88190adf39e85375bd11b |
completed | April 19, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a1bda48190a9cd1db436d4be62 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:45 a.m.