Triple
T33794965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Debbie Blair |
E866044
|
entity |
| Predicate | sharesProfessionDomainWithRelative |
P11874
|
FINISHED |
| Object | entertainment industry (via Linda Blair) |
—
|
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: entertainment industry (via Linda Blair) | Statement: [Debbie Blair, sharesProfessionDomainWithRelative, entertainment industry (via Linda Blair)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesProfessionDomainWithRelative Context triple: [Debbie Blair, sharesProfessionDomainWithRelative, entertainment industry (via Linda Blair)]
-
A.
sharesProfessionWith
Indicates that two entities have the same profession or occupational role.
-
B.
sharesWorkplaceWith
Indicates that two entities work at the same workplace or organization.
-
C.
sharesDomainWith
chosen
Indicates that two entities operate within, belong to, or are associated with the same domain or domain-like scope.
-
D.
sharesWorkWith
Indicates that one entity collaborates or participates jointly in work or tasks with another entity.
-
E.
sharesCompetencesWith
Indicates that two entities possess and can apply the same or overlapping set of skills, abilities, or areas of expertise.
- 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_69f3498f99f481909cb271f4965a7594 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ffc605b0648190a7abe9128b0d857a |
completed | May 9, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69ffc5742d80819099f947ece78d5700 |
completed | May 9, 2026, 11:38 p.m. |
Created at: May 1, 2026, 1:46 a.m.