Triple
T18114353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chief Inspector Hubbard |
E433563
|
entity |
| Predicate | investigatesCrimeType |
P77441
|
FINISHED |
| Object | attempted 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: attempted murder | Statement: [Chief Inspector Hubbard, investigatesCrimeType, attempted murder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: investigatesCrimeType Context triple: [Chief Inspector Hubbard, investigatesCrimeType, attempted murder]
-
A.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
pursuesCrimeType
chosen
Indicates that an entity (such as a law enforcement body or individual) actively investigates, targets, or prosecutes a specified type of crime.
-
C.
regionOfCrimes
Indicates the geographic area or jurisdiction in which the crimes occurred or are attributed to an entity.
-
D.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
-
E.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
- 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddd4c7888190b85c39decdb0333f |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:28 a.m.