Triple
T32163752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bailey |
E821500
|
entity |
| Predicate | professionalRelationshipWith |
P155703
|
FINISHED |
| Object | Destiny |
—
|
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: Destiny | Statement: [Bailey, professionalRelationshipWith, Destiny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalRelationshipWith Context triple: [Bailey, professionalRelationshipWith, Destiny]
-
A.
hasProfessionalRelationshipWith
chosen
Indicates a formal, work-related connection or collaboration exists between the two entities in a professional context.
-
B.
professionalOutcome
Indicates the resulting professional status, achievement, or consequence that arises from a person’s work-related actions, experiences, or decisions.
-
C.
workRelatedTo
Indicates a relationship where one entity’s work, tasks, or professional activities are connected, associated, or relevant to those of another entity.
-
D.
professionalRepresentation
Indicates that one entity formally acts on behalf of or advocates for another in a professional or official capacity.
-
E.
professionalCareer
Indicates the relationship capturing a person’s work-related roles, positions, and progression over time in their occupation or field.
- 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:33 a.m.