Triple
T17514856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cửu Long region |
E426541
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Long Xuyên |
—
|
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: Long Xuyên | Statement: [Cửu Long region, hasCity, Long Xuyên]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Long Xuyên Context triple: [Cửu Long region, hasCity, Long Xuyên]
-
A.
Long Xuyên
chosen
Long Xuyên is a major city in Vietnam’s Mekong Delta region, serving as the capital of An Giang Province and an important economic and cultural center.
-
B.
Tongxiang
Tongxiang is a county-level city in northern Zhejiang Province, China, known for administering the historic water town of Wuzhen.
-
C.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
D.
Changshou
Changshou was a Chinese imperial era name used during the reign of Empress Wu Zetian in the Tang dynasty.
-
E.
Liyang
Liyang is a county-level city in Jiangsu Province, China, known for its scenic attractions such as Tianmu Lake and its administration under the prefecture-level city of Changzhou.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4525fa0c48190b42b36c40db7ed7f |
completed | April 19, 2026, 3:56 a.m. |
Created at: April 10, 2026, 5:49 a.m.