Triple
T21715765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高崎線 |
E536023
|
entity |
| Predicate | 歴史的区分 |
P13759
|
FINISHED |
| Object | 旧日本鉄道本線の一部 |
—
|
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: 旧日本鉄道本線の一部 | Statement: [高崎線, 歴史的区分, 旧日本鉄道本線の一部]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 歴史的区分 Context triple: [高崎線, 歴史的区分, 旧日本鉄道本線の一部]
-
A.
historicallyDistinctFrom
Indicates that two entities are recognized as separate and not the same in historical context, despite any similarities or connections they may have.
-
B.
historicalType
Indicates that one entity classifies or characterizes another in terms of its role, status, or category within a historical context.
-
C.
isHistoricallyDistinctRegion
Indicates that a region is recognized as a separate and distinct territorial or cultural entity in historical context, differing from surrounding or successor regions.
-
D.
historicalClassificationEnd
Indicates the point in time when a particular historical classification or categorization of an entity ceases to be valid.
-
E.
historicallyConsidered
chosen
Indicates that one entity has been regarded or classified in a particular way relative to another entity during a past historical period.
- 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb53761b48190954a46e8155a84f0 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.