Triple
T6913512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cihu Lake scenic area |
E159992
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Daxi District |
E164200
|
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: Daxi District | Statement: [Cihu Lake scenic area, locatedIn, Daxi District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daxi District Context triple: [Cihu Lake scenic area, locatedIn, Daxi District]
-
A.
Daxi District
chosen
Daxi District is a historic district in Taoyuan, Taiwan, known for its preserved old streets, traditional wooden architecture, and cultural heritage.
-
B.
Shenkeng District
Shenkeng District is a suburban district of New Taipei City in northern Taiwan, best known for its historic old street and specialty stinky tofu cuisine.
-
C.
Dawan District
Dawan District is an administrative district in Klungkung Regency on the island of Bali, Indonesia.
-
D.
Dianjun District
Dianjun District is an urban district of Yichang City in Hubei Province, central China, situated along the Yangtze River and known for its role in the region’s transportation and industry.
-
E.
Caidian District
Caidian District is an administrative district in the western part of Wuhan, China, known for its rapid urban development and integration into the city’s metro network.
- 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_69c6883ab1008190a07129ff06f625d9 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d9dbca6c819091d8b65e54ada5d9 |
completed | March 27, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa5cf190819093f3dc9513361e49 |
completed | March 28, 2026, 3:57 p.m. |
Created at: March 27, 2026, 2:25 p.m.