Triple
T11934303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 文京区 |
E283998
|
entity |
| Predicate | hasMajorShrineOrTemple |
P48433
|
FINISHED |
| Object | 湯島天満宮 |
—
|
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: 湯島天満宮 | Statement: [文京区, hasMajorShrineOrTemple, 湯島天満宮]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorShrineOrTemple Context triple: [文京区, hasMajorShrineOrTemple, 湯島天満宮]
-
A.
hasMajorShrine
Indicates that one entity serves as a principal or primary shrine dedicated to another entity.
-
B.
hasShrinesIn
Indicates that one entity possesses or maintains shrines that are located within the area or domain of another entity.
-
C.
majorTempleLocation
Indicates that a major temple associated with an entity is located at a specified place.
-
D.
hasTempleOf
Indicates that a location or entity possesses, contains, or is the site of a temple dedicated to a particular deity, figure, or purpose.
-
E.
hasNotableTemple
chosen
Indicates that an entity is associated with a temple that is recognized as particularly important, famous, or significant.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.