Triple
T31327025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 天王寺公園 |
E798913
|
entity |
| Predicate | locatedNearHistoricSite |
P87975
|
FINISHED |
| Object | 四天王寺 |
—
|
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: 四天王寺 | Statement: [天王寺公園, locatedNearHistoricSite, 四天王寺]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedNearHistoricSite Context triple: [天王寺公園, locatedNearHistoricSite, 四天王寺]
-
A.
locatedInHistoricSite
Indicates that an entity is situated within or on the grounds of a place officially recognized as a historic site.
-
B.
historicallyLocatedNear
Indicates that, in a historical context, one entity was geographically situated close to another entity.
-
C.
hasNearbyHistoricStructure
Indicates that one entity is located close to another entity that is classified as a historic structure.
-
D.
hasNearbyHistoricArea
Indicates that one entity is located close to another entity that is designated as a historic area.
-
E.
hasAdjacentHistoricSite
chosen
Indicates that one place is directly next to or very near another place that is recognized as a historic site.
- 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_69f224e3238c8190b2291f50ea4962cd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a017e7bdfe481909cb4d5bdede6035e |
completed | May 11, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_6a017defee108190bdf5f98dc415b250 |
completed | May 11, 2026, 6:57 a.m. |
Created at: April 29, 2026, 9:15 p.m.