Triple
T5132373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Hutchinson |
E115730
|
entity |
| Predicate | hasRacingNumber |
P59494
|
FINISHED |
| Object | various numbers depending on class and year |
—
|
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: various numbers depending on class and year | Statement: [Ian Hutchinson, hasRacingNumber, various numbers depending on class and year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRacingNumber Context triple: [Ian Hutchinson, hasRacingNumber, various numbers depending on class and year]
-
A.
racingNumber
chosen
Indicates that an entity has been assigned a specific competition or race identification number used to distinguish it from other participants.
-
B.
hasRace
Indicates that an entity possesses or is characterized by a particular race or racial classification.
-
C.
isFromRacingFamily
Indicates that an entity belongs to or originates from a family with a background or tradition in racing.
-
D.
hasRaceClass
Indicates that an entity participates in or is associated with a particular race classification or category.
-
E.
racesEntered
Indicates that an entity has participated in or registered for one or more races.
- 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_69bd444426bc819099ccd23f141e22aa |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:42 p.m.