Triple
T10726337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vancouver Peninsula (various localities) |
E252956
|
entity |
| Predicate | hasAssociatedPersonOccupation |
P83547
|
FINISHED |
| Object | Royal Navy officer |
—
|
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: Royal Navy officer | Statement: [Vancouver Peninsula (various localities), hasAssociatedPersonOccupation, Royal Navy officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedPersonOccupation Context triple: [Vancouver Peninsula (various localities), hasAssociatedPersonOccupation, Royal Navy officer]
-
A.
occupationOfAssociatedPerson
chosen
Indicates the job or professional role held by a person who is associated with another referenced entity.
-
B.
occupationalAssociation
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
C.
isAssociatedWithProfessionOfBearer
Indicates that one entity is connected to, or involved with, the profession or occupational role held by another entity.
-
D.
hasOccupationOfDesignee
Indicates that one entity serves as the designated or appointed holder of an occupation or role for another entity.
-
E.
subjectHasOccupationContext
Indicates that a subject’s occupation is specified or interpreted within a particular contextual framework (such as time, place, or situation).
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fc713f081909ba1d1b986c1fe5c |
completed | April 9, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69d6f309a44881908e49e3ba478c35b4 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:14 p.m.