Triple
T34809833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meursault |
E1003466
|
entity |
| Predicate | isArrestedFor |
P15395
|
FINISHED |
| Object | Murder |
—
|
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: Murder | Statement: [Meursault, isArrestedFor, Murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isArrestedFor Context triple: [Meursault, isArrestedFor, Murder]
-
A.
wasArrested
Indicates that an authority detained and took a person into legal custody in connection with a suspected offense.
-
B.
arrestedFor
chosen
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
C.
wasArrestedAfter
Indicates that one entity was arrested at a point in time later than another specified event or arrest.
-
D.
hasBeenArrestedBy
Indicates that an entity has been taken into custody or formally apprehended by another entity, typically a law enforcement authority.
-
E.
wasArrestedDuring
Indicates that an entity was arrested in the course of, or at the time of, a specified event or activity.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ab248748190858420c09bbdba32 |
completed | May 3, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.