Triple
T16493132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ming De School campus, Liuhe, Taicang, Jiangsu, China |
E400615
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object |
Liuhe
Liuhe is a town in Taicang, Jiangsu Province, China, known as a local residential and educational hub within the greater Suzhou region.
|
E1217559
|
NE FINISHED |
How this triple was built (4 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: Liuhe | Statement: [Ming De School campus, Liuhe, Taicang, Jiangsu, China, locatedIn, Liuhe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liuhe Context triple: [Ming De School campus, Liuhe, Taicang, Jiangsu, China, locatedIn, Liuhe]
-
A.
Lianghe
Lianghe is a town in southwestern China's Yunnan province, known as the seat of Lianghe County within the Dehong Dai and Jingpo Autonomous Prefecture.
-
B.
Zhuanghe
Zhuanghe is a county-level coastal city administered by Dalian in Liaoning Province, northeastern China, known for its agriculture, fishing, and scenic landscapes.
-
C.
Suihua
Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
-
D.
Jinhai
Jinhai is one of the co-pilots of the Jaeger Guardian Bravo in the Pacific Rim universe.
-
E.
Houhai
Houhai is a coastal area in Shenzhen, China, known for its modern waterfront developments, shopping centers, and vibrant nightlife.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Liuhe Triple: [Ming De School campus, Liuhe, Taicang, Jiangsu, China, locatedIn, Liuhe]
Generated description
Liuhe is a town in Taicang, Jiangsu Province, China, known as a local residential and educational hub within the greater Suzhou region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liuhe Target entity description: Liuhe is a town in Taicang, Jiangsu Province, China, known as a local residential and educational hub within the greater Suzhou region.
-
A.
Lianghe
Lianghe is a town in southwestern China's Yunnan province, known as the seat of Lianghe County within the Dehong Dai and Jingpo Autonomous Prefecture.
-
B.
Zhuanghe
Zhuanghe is a county-level coastal city administered by Dalian in Liaoning Province, northeastern China, known for its agriculture, fishing, and scenic landscapes.
-
C.
Suihua
Suihua is a prefecture-level city in northeastern China known for its agricultural production and cold climate.
-
D.
Jinhai
Jinhai is one of the co-pilots of the Jaeger Guardian Bravo in the Pacific Rim universe.
-
E.
Houhai
Houhai is a coastal area in Shenzhen, China, known for its modern waterfront developments, shopping centers, and vibrant nightlife.
- F. None of above. chosen
Provenance (5 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e30cb648190a52cb32896c4ac5a |
completed | April 18, 2026, 7:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00607cbc80819088505d8bdd663109 |
completed | May 10, 2026, 10:39 a.m. |
| NEDg | Description generation | batch_6a00612373808190b8736b0572598d12 |
completed | May 10, 2026, 10:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0061aaa7c48190a56bd52c8dfd6bdc |
completed | May 10, 2026, 10:44 a.m. |
Created at: April 10, 2026, 5:13 a.m.