Triple
T6663659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriel de Montgomery |
E151539
|
entity |
| Predicate | aftermathOfAccident |
P48782
|
FINISHED |
| Object | withdrew temporarily from court |
—
|
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: withdrew temporarily from court | Statement: [Gabriel de Montgomery, aftermathOfAccident, withdrew temporarily from court]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aftermathOfAccident Context triple: [Gabriel de Montgomery, aftermathOfAccident, withdrew temporarily from court]
-
A.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
B.
aftermathOf
chosen
Indicates that one event, state, or condition occurs as a consequence or result following another event.
-
C.
aftermathDescription
Indicates the description or characterization of events, conditions, or consequences that occur following a particular incident or action.
-
D.
accident
Indicates an unintended, unforeseen event or mishap occurring, often resulting in damage, injury, or disruption.
-
E.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
- 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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9d53848190ac75523c157249c6 |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:02 p.m.