Triple
T4205790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irish Kings |
E86179
|
entity |
| Predicate | criminalRole |
P46944
|
FINISHED |
| Object | weapons suppliers |
—
|
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: weapons suppliers | Statement: [Irish Kings, criminalRole, weapons suppliers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: criminalRole Context triple: [Irish Kings, criminalRole, weapons suppliers]
-
A.
roleInCrime
chosen
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
B.
crimeType
Indicates the specific category or nature of the crime associated with an event or entity.
-
C.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
D.
prisonRole
Indicates a role or function that an entity holds within the context or system of a prison.
-
E.
partnerInCrime
Indicates a relationship where two or more entities collaborate closely in committing or planning wrongful, illicit, or mischievous acts together.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03844314819092639ed7d6ef2c6e |
completed | March 9, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69af0196716c81908b99193690630a29 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:49 p.m.