Triple
T23300900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candler v Crane, Christmas & Co |
E590298
|
entity |
| Predicate | professionInvolved |
P69514
|
FINISHED |
| Object | accountants |
—
|
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: accountants | Statement: [Candler v Crane, Christmas & Co, professionInvolved, accountants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionInvolved Context triple: [Candler v Crane, Christmas & Co, professionInvolved, accountants]
-
A.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
B.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
-
C.
includesProfession
chosen
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
-
D.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
E.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d37fd08190ad2d199c54324c02 |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:04 p.m.