Triple
T29032718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Marston |
E737769
|
entity |
| Predicate | transportUsedInCrime |
P193248
|
FINISHED |
| Object | car |
—
|
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: car | Statement: [Anthony Marston, transportUsedInCrime, car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportUsedInCrime Context triple: [Anthony Marston, transportUsedInCrime, car]
-
A.
utilityInvolved
Indicates that a utility service or provider is involved in, associated with, or plays a role in the referenced situation or relationship.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
criminalType
Indicates the specific category or classification of crime associated with a criminal act or offender.
-
D.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
-
E.
perpetratedCrimesIn
Indicates that an entity committed one or more crimes within a specified location or jurisdiction.
- 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_69f077ef00fc81909325f084ad37c035 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
| PDg | Predicate description generation | batch_69fd3d45ccb8819082f15e60bd33afc9 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 28, 2026, 9:56 a.m.