Triple
T29034147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banbury |
E737806
|
entity |
| Predicate | hasNearbyFormulaOnePresence |
P98305
|
FINISHED |
| Object | Haas F1 Team facility |
—
|
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: Haas F1 Team facility | Statement: [Banbury, hasNearbyFormulaOnePresence, Haas F1 Team facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyFormulaOnePresence Context triple: [Banbury, hasNearbyFormulaOnePresence, Haas F1 Team facility]
-
A.
hasNearbyRacetrack
chosen
Indicates that one entity is located close to or in the vicinity of a racetrack.
-
B.
hasNearbyStadium
Indicates that one entity is located close to or in the vicinity of a stadium associated with another entity.
-
C.
hasNearbyPassage
Indicates that one location or object is situated close to a passage, such as a corridor, tunnel, or route, that provides access or transit nearby.
-
D.
enteredFormulaOne
Indicates that an entity began competing in Formula One racing, marking its entry into the Formula One championship.
-
E.
hasNearbyCove
Indicates that one location is situated close to a small sheltered bay or cove.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fddd373cdc8190be1b12e70e4deb1f |
completed | May 8, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69fddc6915a88190ad41e379aa3ede13 |
completed | May 8, 2026, 12:51 p.m. |
Created at: April 28, 2026, 9:57 a.m.