Triple
T11151040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FRIBA |
E263783
|
entity |
| Predicate | professionalStatusIndicated |
P19008
|
FINISHED |
| Object | fellow of a professional architectural body |
—
|
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: fellow of a professional architectural body | Statement: [FRIBA, professionalStatusIndicated, fellow of a professional architectural body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalStatusIndicated Context triple: [FRIBA, professionalStatusIndicated, fellow of a professional architectural body]
-
A.
hasProfessionalStatus
chosen
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
B.
professionalStatusRestriction
Indicates a limitation or condition placed on someone’s professional role, eligibility, or activities.
-
C.
careerStatus
Indicates the current stage, position, or condition of an entity within its professional or occupational life.
-
D.
professionalSince
Indicates the point in time when an entity began its professional activity or career in a given role or field.
-
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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.