Triple
T25409723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peddle Thorp |
E636657
|
entity |
| Predicate | hasProfessionalCategory |
P110532
|
FINISHED |
| Object | Australian architects |
—
|
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: Australian architects | Statement: [Peddle Thorp, hasProfessionalCategory, Australian architects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalCategory Context triple: [Peddle Thorp, hasProfessionalCategory, Australian architects]
-
A.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
B.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
C.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
-
D.
hasProfessionalGroup
chosen
Indicates that an entity belongs to, is associated with, or is categorized under a particular professional group or category.
-
E.
hasProfessionalComponent
Indicates that something includes, involves, or is associated with a professional (work- or career-related) element or aspect.
- 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_69e75db361d881908d8701c856da6413 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6b903538481909cffcb6cc1cc0e70 |
completed | May 3, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69f6b626120c819097c9ad04487570d7 |
completed | May 3, 2026, 2:42 a.m. |
Created at: April 21, 2026, 1:53 p.m.