Triple
T34427502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack Trainer |
E883728
|
entity |
| Predicate | professionalAllyOf |
P155703
|
FINISHED |
| Object | Tess McGill |
—
|
NE NERFINISHED |
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: Tess McGill | Statement: [Jack Trainer, professionalAllyOf, Tess McGill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalAllyOf Context triple: [Jack Trainer, professionalAllyOf, Tess McGill]
-
A.
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.
-
B.
partnerInProfession
Indicates that two or more entities share a professional partnership or collaborate together within the same occupation or field.
-
C.
professionalMembership
Indicates that an entity holds membership or affiliation in a professional organization, association, or body.
-
D.
hasProfessionalRelationshipWith
chosen
Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
-
E.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
- 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_69f349c3dd2c819092cc9e64809f4a42 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2 a.m.