Triple
T29073393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yorkshire militia system |
E735867
|
entity |
| Predicate | subdivisionPrinciple |
P167943
|
FINISHED |
| Object | riding level |
—
|
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: riding level | Statement: [Yorkshire militia system, subdivisionPrinciple, riding level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionPrinciple Context triple: [Yorkshire militia system, subdivisionPrinciple, riding level]
-
A.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
-
B.
subdivisionFlagOf
Indicates that one administrative or territorial unit is a designated subdivision or sub-part of another unit.
-
C.
subdivisionFactor
Indicates how many smaller parts or segments a whole entity is divided into within a given context.
-
D.
traditionalSubdivisionOf
Indicates that one entity is a historically or culturally recognized sub-unit or component region of another, according to traditional (rather than strictly modern administrative) divisions.
-
E.
subdivisionType0
Indicates that the referenced entity is classified as the primary (level 0) type of administrative or territorial subdivision within a larger jurisdiction.
- F. None of above. chosen
Provenance (4 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_69f077e9b0a48190bb79548279cb7f64 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 10:21 a.m.