Triple
T3805054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanzōmon area |
E91784
|
entity |
| Predicate | nearbyInstitutionType |
P303
|
FINISHED |
| Object | ministries |
—
|
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: ministries | Statement: [Hanzōmon area, nearbyInstitutionType, ministries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyInstitutionType Context triple: [Hanzōmon area, nearbyInstitutionType, ministries]
-
A.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
B.
adjacentToCampusOf
Indicates that one entity is located next to or directly bordering the campus area of another entity.
-
C.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
D.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
E.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
- 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_69aed96354f48190a768966d6bd19b04 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8db8a288190afd1e3b9dcf02e97 |
completed | March 9, 2026, 3:35 p.m. |
| PD | Predicate disambiguation | batch_69aee7461abc8190945716f4b93e1a18 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:15 p.m.