Triple
T37534862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McLaren M8D |
E933167
|
entity |
| Predicate | testingAccidentVictim |
P52515
|
FINISHED |
| Object | Bruce McLaren |
—
|
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: Bruce McLaren | Statement: [McLaren M8D, testingAccidentVictim, Bruce McLaren]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: testingAccidentVictim Context triple: [McLaren M8D, testingAccidentVictim, Bruce McLaren]
-
A.
testingAccidentYear
Indicates a relationship where an accident is associated with, or evaluated in the context of, a specific year designated as its accident year.
-
B.
testingAccidentCountry
Indicates the country in which a testing-related accident occurred.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
hasInjuredPerson
chosen
Indicates that an entity has a person who has been harmed or injured associated with it.
-
E.
hasFictionalAccident
Indicates that an entity experiences or is involved in an accident that occurs within a fictional or imagined context.
- 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.