Triple
T21519934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 都筑郡 |
E530945
|
entity |
| Predicate | 旧郡役所所在地 |
P13121
|
FINISHED |
| Object | 神奈川県 |
—
|
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: 神奈川県 | Statement: [都筑郡, 旧郡役所所在地, 神奈川県]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 旧郡役所所在地 Context triple: [都筑郡, 旧郡役所所在地, 神奈川県]
-
A.
originatedAsDaimyoResidence
Indicates that something began its existence or function as the residence of a daimyo.
-
B.
locatedInPresentDayMunicipality
Indicates that an entity is situated within the boundaries of a specific municipality as it exists in the present day, regardless of historical administrative changes.
-
C.
所在地_市区町村
Indicates the municipality (city, ward, town, or village) in which an entity is located.
-
D.
hasHistoricCountySeat
chosen
Indicates that an administrative region historically had its county government or main county offices located in a particular settlement or city.
-
E.
locatedInFormerNamePlace
Indicates that an entity is located in a place that is referred to by its former or historical name rather than its current name.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee884af0f08190bc1f3d70e57a325d |
completed | April 26, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:26 p.m.