Triple
T5736372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. King Schultz |
E126512
|
entity |
| Predicate | professionSkill |
P58200
|
FINISHED |
| Object | tracking fugitives |
—
|
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: tracking fugitives | Statement: [Dr. King Schultz, professionSkill, tracking fugitives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionSkill Context triple: [Dr. King Schultz, professionSkill, tracking fugitives]
-
A.
skillSet
chosen
Indicates that an entity possesses or is associated with a particular collection of skills or competencies.
-
B.
professionalScope
Indicates the range of activities, responsibilities, or roles that fall within a person’s or organization’s recognized professional duties or expertise.
-
C.
skillEmphasis
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
D.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
E.
skillAssessed
Indicates that an entity’s skill or competency has been evaluated or measured, typically by another agent or process.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255ad6f48190977bf4f037110aa3 |
completed | March 22, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69c021c8195481909419808b002628aa |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.