Triple
T2675827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kamo River |
E56456
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Gion district |
E83963
|
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: Gion district | Statement: [Kamo River, adjacentTo, Gion district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gion district Context triple: [Kamo River, adjacentTo, Gion district]
-
A.
Gion district
chosen
Gion district is Kyoto’s famous traditional entertainment quarter, renowned for its historic wooden machiya houses, teahouses, and geisha (geiko and maiko) culture.
-
B.
Umeda district
Umeda district is a major commercial and transportation hub in Osaka, Japan, known for its skyscrapers, shopping complexes, and extensive train and subway connections.
-
C.
Susukino district
Susukino district is Sapporo’s famous entertainment quarter, known for its dense concentration of bars, restaurants, nightlife, and neon-lit streets.
-
D.
Arashiyama district
Arashiyama district is a scenic area on the western outskirts of Kyoto, Japan, famed for its bamboo groves, historic temples, and iconic Togetsukyo Bridge.
-
E.
Shimokitazawa district
Shimokitazawa district is a trendy Tokyo neighborhood known for its narrow streets packed with vintage clothing shops, small theaters, live music venues, and independent cafes.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9b3530c819093942cc985f814ef |
completed | March 7, 2026, 7:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44ec039e881909660350b98d79ba1 |
completed | March 13, 2026, 5:52 p.m. |
Created at: March 6, 2026, 9:54 p.m.