Triple
T10426445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Cinema Editors |
E245800
|
entity |
| Predicate | professionalFocus |
P62124
|
FINISHED |
| Object | post-production |
—
|
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: post-production | Statement: [American Cinema Editors, professionalFocus, post-production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalFocus Context triple: [American Cinema Editors, professionalFocus, post-production]
-
A.
professionalScope
Indicates the range of activities, responsibilities, or roles that fall within a person’s or organization’s recognized professional duties or expertise.
-
B.
professionalSector
chosen
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
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.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
E.
professionalBody
Indicates that an entity is a formal organization that represents, regulates, or supports members of a particular profession.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea498ab08190b451c0b257c0711b |
completed | April 7, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:12 p.m.