Triple
T25316609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The File on Thelma Jordon |
E634760
|
entity |
| Predicate | crimeTypeDepicted |
P7957
|
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: [The File on Thelma Jordon, crimeTypeDepicted, murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crimeTypeDepicted Context triple: [The File on Thelma Jordon, crimeTypeDepicted, murder]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
C.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
D.
crimeCharged
Indicates that legal authorities have formally accused an entity of committing a specific crime.
-
E.
depictsMotive
Indicates that one entity visually represents or illustrates the motive, intention, or underlying reason associated with another entity or action.
- 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_69e75a9847c08190bb02990d06d5ffb7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f49689e50881909c13a48de497e74f |
completed | May 1, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:28 p.m.