Triple
T11623987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanchong |
E276212
|
entity |
| Predicate | hasNotableDistrict |
P295
|
FINISHED |
| Object |
Shunqing District
Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
|
E946585
|
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: Shunqing District | Statement: [Nanchong, hasNotableDistrict, Shunqing District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shunqing District Context triple: [Nanchong, hasNotableDistrict, Shunqing District]
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Yicheng District
Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
-
C.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
D.
Sanzhi District
Sanzhi District is a rural coastal district in northern Taiwan known for its scenic landscapes, hot springs, and agricultural produce within New Taipei City.
-
E.
Zhengxiang District
Zhengxiang District is an urban administrative district of Hengyang City in Hunan Province, China, known for its role as one of the city's central built-up areas.
- 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: Shunqing District Triple: [Nanchong, hasNotableDistrict, Shunqing District]
Generated description
Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shunqing District Target entity description: Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
-
A.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
B.
Yicheng District
Yicheng District is an urban administrative district under the jurisdiction of Zaozhuang City in Shandong Province, eastern China.
-
C.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
D.
Sanzhi District
Sanzhi District is a rural coastal district in northern Taiwan known for its scenic landscapes, hot springs, and agricultural produce within New Taipei City.
-
E.
Zhengxiang District
Zhengxiang District is an urban administrative district of Hengyang City in Hunan Province, China, known for its role as one of the city's central built-up areas.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a122a3708190ab6513dad4c4fde7 |
completed | April 10, 2026, 7:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f08fa01ba88190a4fa5a74fe96cfa9 |
completed | April 28, 2026, 10:44 a.m. |
| NEDg | Description generation | batch_69f0a7971df48190b51c1d245f4c89d2 |
completed | April 28, 2026, 12:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f0d61cf9c4819080590fefc60f7325 |
completed | April 28, 2026, 3:45 p.m. |
Created at: April 8, 2026, 9:39 p.m.