Triple
T16061346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gu'an County |
E389618
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Gu'an Xian |
E389618
|
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: Gu'an Xian | Statement: [Gu'an County, romanization, Gu'an Xian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gu'an Xian Context triple: [Gu'an County, romanization, Gu'an Xian]
-
A.
Wan'an County
Wan'an County is an administrative county under the jurisdiction of Ji'an City in Jiangxi Province, southeastern China.
-
B.
Gu'an County
chosen
Gu'an County is an administrative county in northern China’s Hebei Province, situated just south of Beijing and forming part of the capital’s greater metropolitan area.
-
C.
Shixing County
Shixing County is an administrative county under the jurisdiction of Shaoguan City in northern Guangdong Province, China, known for its mountainous terrain and rural landscapes.
-
D.
Anxi County
Anxi County is a county in Fujian Province, China, renowned as one of the country’s most famous tea-producing regions, especially for Tieguanyin oolong tea.
-
E.
Anji County
Anji County is a scenic county in Zhejiang Province, China, renowned for its extensive bamboo forests and eco-tourism.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183795100819097be92e6d07dc5b1 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f39008c819095ad8512eb119ee8 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 4:57 a.m.