Triple
T12327150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanping |
E293860
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Yanping District
Yanping District is the central urban district and administrative seat of Nanping City in Fujian Province, China.
|
E1002094
|
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: Yanping District | Statement: [Nanping, hasDistrict, Yanping District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yanping District Context triple: [Nanping, hasDistrict, Yanping District]
-
A.
Yuhui District
Yuhui District is an urban administrative district within the prefecture-level city of Bengbu in Anhui Province, China.
-
B.
Shizhong District
Shizhong District is an urban administrative district that serves as the central area of Zaozhuang City in Shandong Province, China.
-
C.
Baihe District
Baihe District is a rural district in Tainan, Taiwan, known for its scenic landscapes and popular hot spring resorts.
-
D.
Xiuying District
Xiuying District is an urban administrative district of Haikou City on Hainan Island in southern China, known for its coastal location and role in the city's development.
-
E.
Chengzhong District
Chengzhong District is a central urban district of Xining, the capital city of Qinghai Province in northwest 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: Yanping District Triple: [Nanping, hasDistrict, Yanping District]
Generated description
Yanping District is the central urban district and administrative seat of Nanping City in Fujian Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yanping District Target entity description: Yanping District is the central urban district and administrative seat of Nanping City in Fujian Province, China.
-
A.
Yuhui District
Yuhui District is an urban administrative district within the prefecture-level city of Bengbu in Anhui Province, China.
-
B.
Shizhong District
Shizhong District is an urban administrative district that serves as the central area of Zaozhuang City in Shandong Province, China.
-
C.
Baihe District
Baihe District is a rural district in Tainan, Taiwan, known for its scenic landscapes and popular hot spring resorts.
-
D.
Xiuying District
Xiuying District is an urban administrative district of Haikou City on Hainan Island in southern China, known for its coastal location and role in the city's development.
-
E.
Chengzhong District
Chengzhong District is a central urban district of Xining, the capital city of Qinghai Province in northwest 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4f90a881908c5060dd197744d1 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684d0315c8190988431785a7b1e1e |
completed | May 2, 2026, 11:12 p.m. |
| NEDg | Description generation | batch_69f686b5fbe48190b365d53db3df80ce |
completed | May 2, 2026, 11:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f68713097881908f3f35b1c7814f60 |
completed | May 2, 2026, 11:21 p.m. |
Created at: April 8, 2026, 9:53 p.m.