Triple
T14124313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xinzhou |
E339987
|
entity |
| Predicate | hasAdministrativeCenter |
P1474
|
FINISHED |
| Object |
Xinfu District
Xinfu District is an urban administrative district that serves as the central area and seat of government for Xinzhou in Shanxi Province, China.
|
E1153938
|
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: Xinfu District | Statement: [Xinzhou, hasAdministrativeCenter, Xinfu District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinfu District Context triple: [Xinzhou, hasAdministrativeCenter, Xinfu District]
-
A.
Tiefeng District
Tiefeng District is an urban district of the city of Qiqihar in Heilongjiang Province, northeastern China.
-
B.
Yushui District
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
-
C.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
D.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
-
E.
Shuangxi District
Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
- 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: Xinfu District Triple: [Xinzhou, hasAdministrativeCenter, Xinfu District]
Generated description
Xinfu District is an urban administrative district that serves as the central area and seat of government for Xinzhou in Shanxi Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xinfu District Target entity description: Xinfu District is an urban administrative district that serves as the central area and seat of government for Xinzhou in Shanxi Province, China.
-
A.
Tiefeng District
Tiefeng District is an urban district of the city of Qiqihar in Heilongjiang Province, northeastern China.
-
B.
Yushui District
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
-
C.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
D.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong Province, China.
-
E.
Shuangxi District
Shuangxi District is a rural, mountainous district in eastern New Taipei City, Taiwan, known for its rivers, old streets, and natural scenery.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6096976481909dc79066c5165a50 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff13322c548190bac21db2bfa56ee9 |
completed | May 9, 2026, 10:57 a.m. |
| NEDg | Description generation | batch_69ff14042ce8819084817836b096f175 |
completed | May 9, 2026, 11:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff14745a8c81909b10d6b21b88b50b |
completed | May 9, 2026, 11:03 a.m. |
Created at: April 9, 2026, 10:22 p.m.