Triple
T23927025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbia District |
E602385
|
entity |
| Predicate | majorPost |
P70206
|
FINISHED |
| Object | Fort Vancouver |
—
|
NE NERFINISHED |
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: Fort Vancouver | Statement: [Columbia District, majorPost, Fort Vancouver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorPost Context triple: [Columbia District, majorPost, Fort Vancouver]
-
A.
major
Indicates that one entity is the primary field of academic specialization or main area of study for another entity.
-
B.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
-
C.
majorSee
chosen
Indicates that one entity serves as the primary or most important location where another entity is based, operates, or is centered.
-
D.
majorStatus
Indicates that an entity holds primary or most significant status relative to others in a given context.
-
E.
majorType
Indicates that one entity is classified as the primary or main type/category of another entity.
- 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_69e2953b928c819095395fa87baca583 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cf1e13e8819096432b8133c7d71e |
completed | April 29, 2026, 9:27 a.m. |
| PD | Predicate disambiguation | batch_69f16151ebdc819086e9e1d7cc1f4f3c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:48 p.m.