Triple
T18080385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xin’an |
E432671
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Xin’an Ancient Town |
—
|
NE NERFINISHED |
How this triple was built (3 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: Xin’an Ancient Town | Statement: [Xin’an, alsoKnownAs, Xin’an Ancient Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xin’an Ancient Town Context triple: [Xin’an, alsoKnownAs, Xin’an Ancient Town]
-
A.
Jinxi Ancient Town
Jinxi Ancient Town is a historic water town in Jiangsu Province, China, known for its ancient bridges, canals, and well-preserved traditional architecture.
-
B.
Qibao Ancient Town
Qibao Ancient Town is a historic water town in Shanghai known for its preserved traditional architecture, canals, and bustling old streets filled with shops and street food.
-
C.
Qingyan Ancient Town
Qingyan Ancient Town is a well-preserved historic settlement in Guizhou, China, known for its traditional Ming and Qing dynasty architecture, stone-paved streets, and rich cultural heritage.
-
D.
Huishan Ancient Town
Huishan Ancient Town is a historic water-town district in Wuxi, China, known for its traditional architecture, ancestral halls, and well-preserved Jiangnan cultural heritage.
-
E.
Wutongqiao ancient town
Wutongqiao ancient town is a historic riverside settlement in Leshan, Sichuan, known for its traditional architecture, old streets, and preserved cultural heritage.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xin’an Ancient Town Target entity description: Xin’an Ancient Town is a historic riverside settlement in China known for its well-preserved traditional architecture, ancient streets, and cultural heritage.
-
A.
Jinxi Ancient Town
Jinxi Ancient Town is a historic water town in Jiangsu Province, China, known for its ancient bridges, canals, and well-preserved traditional architecture.
-
B.
Qibao Ancient Town
Qibao Ancient Town is a historic water town in Shanghai known for its preserved traditional architecture, canals, and bustling old streets filled with shops and street food.
-
C.
Qingyan Ancient Town
Qingyan Ancient Town is a well-preserved historic settlement in Guizhou, China, known for its traditional Ming and Qing dynasty architecture, stone-paved streets, and rich cultural heritage.
-
D.
Huishan Ancient Town
Huishan Ancient Town is a historic water-town district in Wuxi, China, known for its traditional architecture, ancestral halls, and well-preserved Jiangnan cultural heritage.
-
E.
Wutongqiao ancient town
Wutongqiao ancient town is a historic riverside settlement in Leshan, Sichuan, known for its traditional architecture, old streets, and preserved cultural heritage.
- F. None of above. chosen
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_69d8b907d05c819083cc3bd6021089e6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4d9fa080081909e1a05e98185a026 |
completed | April 19, 2026, 1:34 p.m. |
Created at: April 10, 2026, 10:27 a.m.