Triple
T5820424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre-Charles Villeneuve |
E129092
|
entity |
| Predicate | deathCauseUncertainty |
P67150
|
FINISHED |
| Object | possibly suicide |
—
|
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: possibly suicide | Statement: [Pierre-Charles Villeneuve, deathCauseUncertainty, possibly suicide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deathCauseUncertainty Context triple: [Pierre-Charles Villeneuve, deathCauseUncertainty, possibly suicide]
-
A.
deathPlace_uncertain
Indicates that the place where an entity died is not known with certainty or is disputed.
-
B.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
C.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
-
D.
deathOutcome
Indicates that an event, condition, or action results in the death of the affected entity.
-
E.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
- F. None of above. chosen
Provenance (4 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_69c0084869e881908d7859492183ca7b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0400f1af881908d376ea4793f6dea |
completed | March 22, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69c0333fdd7081908d829265caa2ac11 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c0400dbec08190b2ef73689b2c0c31 |
completed | March 22, 2026, 7:16 p.m. |
Created at: March 22, 2026, 3:53 p.m.