Triple
T15645667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongmen |
E376169
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Da’an District |
—
|
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: Da’an District | Statement: [Dongmen, locatedIn, Da’an District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Da’an District Context triple: [Dongmen, locatedIn, Da’an District]
-
A.
Da’an District
Da’an District is a central and affluent urban district in Taipei, Taiwan, known for its major commercial areas, universities, and the large Da’an Forest Park.
-
B.
Da'an District
chosen
Da'an District is an urban administrative district within the prefecture-level city of Zigong in Sichuan Province, China, known for its role in the region’s industrial and urban development.
-
C.
Dawan District
Dawan District is an administrative district in Klungkung Regency on the island of Bali, Indonesia.
-
D.
Huadu District
Huadu District is a suburban district in the northern part of Guangzhou, China, known for its growing urban development and transportation links, including metro and rail connections.
-
E.
Yu’an District
Yu’an District is an urban administrative district under the jurisdiction of Lu’an City in Anhui Province, China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
Created at: April 10, 2026, 4:15 a.m.