Triple
T18145608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Blackwood |
E434379
|
entity |
| Predicate | hasPartInHisBusiness |
P110112
|
FINISHED |
| Object | retail bookshop |
—
|
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: retail bookshop | Statement: [William Blackwood, hasPartInHisBusiness, retail bookshop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInHisBusiness Context triple: [William Blackwood, hasPartInHisBusiness, retail bookshop]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasBusinessIn
Indicates that one entity conducts, operates, or maintains business activities within the jurisdiction, location, or domain of another entity.
-
C.
hasBusinesses
chosen
Indicates that an entity owns, operates, or is associated with one or more businesses.
-
D.
hasBusinessSection
Indicates that an entity (such as a publication or website) includes a dedicated section focused on business-related content or topics.
-
E.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de33921c8190b6f645ca63fd146b |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:29 a.m.