Triple
T8788385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Léopoldine Hugo |
E209098
|
entity |
| Predicate | diedInAccidentWith |
P32122
|
FINISHED |
| Object | Charles Vacquerie |
—
|
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: Charles Vacquerie | Statement: [Léopoldine Hugo, diedInAccidentWith, Charles Vacquerie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diedInAccidentWith Context triple: [Léopoldine Hugo, diedInAccidentWith, Charles Vacquerie]
-
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.
murderedAlongWith
Indicates that one entity was killed in the same incident or event as another entity.
-
C.
deathBy
Indicates a relationship where one entity’s death is caused by another entity, event, or factor.
-
D.
deathResultedIn
Indicates that one event, action, or condition caused or led directly to a particular death as its outcome.
-
E.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f89a84c819085d4cfe4e6dfbda8 |
completed | March 31, 2026, 11:58 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1d48f08190b325a77d4c76d223 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:43 p.m.