Triple
T12832988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 八坂神社 |
E306833
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | 円山公園 |
E744618
|
NE 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: 円山公園 | Statement: [八坂神社, locatedNear, 円山公園]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 円山公園 Context triple: [八坂神社, locatedNear, 円山公園]
-
A.
Shikishima Park
Shikishima Park is a large public park in Maebashi, Japan, known for its expansive green spaces, seasonal flowers, and recreational facilities.
-
B.
Asukayama Park
Asukayama Park is a historic public park in Tokyo known for its cherry blossoms, scenic hilltop views, and role as one of Japan’s earliest modern parks.
-
C.
Kitanomaru Park
Kitanomaru Park is a public park in central Tokyo known for its historic grounds, museums, and tranquil green spaces adjacent to the Tokyo Imperial Palace.
-
D.
Inokashira Onshi Park
Inokashira Onshi Park is a popular public park in Tokyo known for its central pond with boat rentals, cherry blossoms, and the nearby Ghibli Museum.
-
E.
Maruyama Park
chosen
Maruyama Park is a popular public park in Sapporo, Japan, known for its cherry blossoms, sports facilities, and proximity to Hokkaido Shrine and Mount Maruyama.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96fb0bb208190bdc4d3dc7909be06 |
completed | April 10, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed8d20081908e0fb5262b354cab |
completed | May 2, 2026, 11:55 p.m. |
Created at: April 9, 2026, 5:34 p.m.