Triple
T23528090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yanta Campus |
E576487
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object | Yanta 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: Yanta District | Statement: [Yanta Campus, district, Yanta District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yanta District Context triple: [Yanta Campus, district, Yanta District]
-
A.
Yanta District
chosen
Yanta District is an urban district of Xi'an in Shaanxi Province, China, known for its cultural and historical landmarks and educational institutions.
-
B.
Anta District
Anta District is an administrative district in the Ancash Region of Peru, known for its Andean highland landscapes and proximity to the city of Huaraz.
-
C.
Anta District
Anta District is an administrative district in southern Peru, located within the Cusco Region and serving as part of Anta Province.
-
D.
Anta District
Anta District is an administrative district located within Acobamba Province in the Huancavelica region of Peru.
-
E.
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.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac758038819098f5f597be39274e |
completed | April 29, 2026, 7 a.m. |
Created at: April 17, 2026, 6:09 p.m.