Triple
T18589715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lew Harper |
E454329
|
entity |
| Predicate | professionAttribute |
P132703
|
FINISHED |
| Object | works alone |
—
|
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: works alone | Statement: [Lew Harper, professionAttribute, works alone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionAttribute Context triple: [Lew Harper, professionAttribute, works alone]
-
A.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
B.
professionalOutcome
Indicates the resulting professional status, achievement, or consequence that arises from a person’s work-related actions, experiences, or decisions.
-
C.
professionalWins
Indicates that one entity has achieved a certain number of victories or successes in a professional context, such as in a career, competition, or formal domain.
-
D.
professionalCompetence
Indicates that one entity possesses the necessary skills, knowledge, and ability to perform a professional role or task to an acceptable standard in relation to another entity or context.
-
E.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b4a2a0819098047ee81278bd9d |
completed | April 19, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:44 a.m.