Triple
T34939116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Bede's Grammar School, Bradford |
E1007666
|
entity |
| Predicate | hasFormerPupilOccupation |
P107616
|
FINISHED |
| Object | novelist |
—
|
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: novelist | Statement: [St Bede's Grammar School, Bradford, hasFormerPupilOccupation, novelist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerPupilOccupation Context triple: [St Bede's Grammar School, Bradford, hasFormerPupilOccupation, novelist]
-
A.
hasFormerPupilRole
Indicates that an entity previously held the role or position of a pupil or student in relation to another entity.
-
B.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
C.
hasFormerInstitutionType
Indicates that an entity was previously associated with or classified under a particular type of institution.
-
D.
hasFormerInstitution
Indicates that an entity was previously affiliated with, employed by, or enrolled in a particular institution in the past.
-
E.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe189fec148190aeef51b417ba15b0 |
completed | May 8, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69fe17285b0881908de7569d8dbd20bd |
completed | May 8, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4 p.m.