Triple
T26744720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 防府天満宮 |
E674361
|
entity |
| Predicate | 社格・評価 |
P161188
|
FINISHED |
| Object | 著名な天満宮の一つ |
—
|
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: 著名な天満宮の一つ | Statement: [防府天満宮, 社格・評価, 著名な天満宮の一つ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 社格・評価 Context triple: [防府天満宮, 社格・評価, 著名な天満宮の一つ]
-
A.
collectionReputation
Indicates the perceived quality, trustworthiness, or status associated with a particular collection based on others’ evaluations or interactions.
-
B.
classRating
Indicates the evaluative score or quality assessment assigned to a class, typically reflecting performance, satisfaction, or overall perceived value.
-
C.
scoringReputation
Indicates that one entity evaluates and assigns a reputation-related score to another entity based on its behavior or performance.
-
D.
crowdReputation
Indicates the collective opinion or perceived standing of an entity as judged by a group or general audience.
-
E.
ratingContext
Indicates the situational or contextual factors under which a rating is given or applies.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f618820b408190b201bc034b4ebee9 |
completed | May 2, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f6106d346c8190868489f36c65b6ec |
completed | May 2, 2026, 2:55 p.m. |
Created at: April 27, 2026, 3:51 a.m.