Triple
T15059795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winston Wolfe |
E379593
|
entity |
| Predicate | problemTypeSpecialization |
P83422
|
FINISHED |
| Object | criminal emergencies |
—
|
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: criminal emergencies | Statement: [Winston Wolfe, problemTypeSpecialization, criminal emergencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: problemTypeSpecialization Context triple: [Winston Wolfe, problemTypeSpecialization, criminal emergencies]
-
A.
problemType
chosen
Indicates the specific category or classification of a problem within a defined problem space or system.
-
B.
problemTypeSolved
Indicates that a given problem has been successfully solved or resolved by a particular entity or method.
-
C.
typicalProblem
Indicates that a situation, issue, or obstacle is representative or characteristic of the usual problems encountered in a given context.
-
D.
propertyTypeSpecialization
Indicates that one property type is a more specific or specialized version of another, more general property type.
-
E.
branchSpecialization
Indicates that one branch or subdivision is specialized or focused in a particular area, function, or domain relative to others.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee50afc8190bf7b0f4bbe8c60a3 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:01 a.m.