Triple
T14002414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Changzhi |
E336861
|
entity |
| Predicate | hasCitySeat |
P15001
|
FINISHED |
| Object |
Lucheng District
Lucheng District is the central urban district and administrative seat of Changzhi, a prefecture-level city in Shanxi Province, China.
|
E1138378
|
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: Lucheng District | Statement: [Changzhi, hasCitySeat, Lucheng District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucheng District Context triple: [Changzhi, hasCitySeat, Lucheng District]
-
A.
Lucheng District
Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
-
B.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
C.
Licheng District
Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
-
D.
Shuocheng District
Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
-
E.
Yicheng District
Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
- 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: Lucheng District Triple: [Changzhi, hasCitySeat, Lucheng District]
Generated description
Lucheng District is the central urban district and administrative seat of Changzhi, a prefecture-level city in Shanxi Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lucheng District Target entity description: Lucheng District is the central urban district and administrative seat of Changzhi, a prefecture-level city in Shanxi Province, China.
-
A.
Lucheng District
Lucheng District is the central urban district and administrative, commercial, and cultural core of Wenzhou in Zhejiang Province, China.
-
B.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
C.
Licheng District
Licheng District is a central urban district of Quanzhou in Fujian Province, China, known for its historic architecture and cultural heritage.
-
D.
Shuocheng District
Shuocheng District is the central urban district and administrative heart of Shuozhou City in Shanxi Province, China.
-
E.
Yicheng District
Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
- 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_69d81c645c5c8190b1fd16a285a1b78a |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ed06a50819093ddc64f55050689 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7cccd548190b9ec93f9d9d2f2af |
completed | May 9, 2026, 4:27 a.m. |
| NEDg | Description generation | batch_69feb971df248190bccc187517557373 |
completed | May 9, 2026, 4:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb9faeb2c819098e8dd4e0cf223bc |
completed | May 9, 2026, 4:37 a.m. |
Created at: April 9, 2026, 10:19 p.m.