Triple
T9767321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanzhong |
E237028
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Hantai District |
E821485
|
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: Hantai District | Statement: [Hanzhong, hasDistrict, Hantai District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hantai District Context triple: [Hanzhong, hasDistrict, Hantai District]
-
A.
Hantai District
chosen
Hantai District is the central urban district and administrative heart of Hanzhong in southern Shaanxi Province, China.
-
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.
Daowai District
Daowai District is an urban district of Harbin in Heilongjiang Province, China, known for its historic architecture and traditional neighborhoods.
-
D.
Kaifu District
Kaifu District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
E.
Shimen District
Shimen District is a rural coastal district in northern Taiwan known for its scenic shoreline, historic sites, and role as part of New Taipei City.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a2da648190836916a45d2998d7 |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc46f170819081ecc5e85a0514c3 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:25 p.m.