Triple
T1695726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiyan |
E36652
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Maojian District |
E217782
|
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: Maojian District | Statement: [Shiyan, hasDistrict, Maojian District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maojian District Context triple: [Shiyan, hasDistrict, Maojian District]
-
A.
Maojian District
chosen
Maojian District is the central urban district and administrative seat of Shiyan, a prefecture-level city in Hubei Province, China.
-
B.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
C.
Qingshan District
Qingshan District is an urban district of Wuhan in Hubei Province, China, known for its heavy industry and riverside location along the Yangtze River.
-
D.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
E.
Tianxin District
Tianxin District is a central urban district of Changsha, the capital city of Hunan Province in China, known for its historical sites and commercial areas.
- 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_69a886163dec8190859c514232a37a05 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa62b645a081909dafdf7a32f2a389 |
completed | March 6, 2026, 5:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb96d12481908f8d7d5c9f1f103f |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:30 p.m.