Triple
T5243475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon |
E118401
|
entity |
| Predicate | roleInGang |
P62350
|
FINISHED |
| Object | central member |
—
|
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: central member | Statement: [Lisbon, roleInGang, central member]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInGang Context triple: [Lisbon, roleInGang, central member]
-
A.
roleInCrime
Indicates the specific function, responsibility, or participation an entity has within the commission of a particular crime.
-
B.
prisonRole
Indicates a role or function that an entity holds within the context or system of a prison.
-
C.
partnerInCrime
Indicates a relationship where two or more entities collaborate closely in committing or planning wrongful, illicit, or mischievous acts together.
-
D.
roleInMutiny
Indicates that one entity participated in a mutiny with a specific role or capacity in that rebellious action.
-
E.
roleInOperationJustCause
Indicates that an entity participated in or held a specific role during Operation Just Cause.
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b4da7308190856cdcee9cca41eb |
completed | March 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69bd77c1397c8190a7fd844d7a396e54 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd79e9d794819097bb628c603d14af |
completed | March 20, 2026, 4:46 p.m. |
Created at: March 20, 2026, 1:49 p.m.