Triple
T22804841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Britten |
E564502
|
entity |
| Predicate | carAccidentInvolves |
P32122
|
FINISHED |
| Object | family |
—
|
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: family | Statement: [Michael Britten, carAccidentInvolves, family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carAccidentInvolves Context triple: [Michael Britten, carAccidentInvolves, family]
-
A.
involvedInAccident
chosen
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
B.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
-
C.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
D.
accidentType
Indicates the specific category or kind of accident associated with an event or incident.
-
E.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
- 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_69e245823f4c8190ade442cdcc2c224a |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d5b37cc8190a41d8f304ba8d609 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:31 p.m.