Triple
T26852699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebring, Florida |
E676100
|
entity |
| Predicate | racewayBuiltOn |
P162825
|
FINISHED |
| Object | former Hendricks Army Airfield |
—
|
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: former Hendricks Army Airfield | Statement: [Sebring, Florida, racewayBuiltOn, former Hendricks Army Airfield]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racewayBuiltOn Context triple: [Sebring, Florida, racewayBuiltOn, former Hendricks Army Airfield]
-
A.
racecourseFeature
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
-
B.
racecourseUsed
Indicates that a particular racecourse is utilized or employed for a given event, activity, or purpose.
-
C.
racecourseType
Indicates the specific kind or classification of a racecourse associated with an entity.
-
D.
raceTrack
Indicates that one entity serves as a race track or racing course used by another entity for racing activities.
-
E.
formerRacecourse
Indicates that a location previously functioned as a racecourse but no longer serves that purpose.
- 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_69eee9b9d7708190a15d7485709ae981 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f62e4168a48190b45268f922780da6 |
completed | May 2, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
| PDg | Predicate description generation | batch_69f62d5268ac8190835dc7119353b840 |
completed | May 2, 2026, 4:58 p.m. |
Created at: April 27, 2026, 5:18 a.m.