Triple
T5831481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fuzhou |
E129358
|
entity |
| Predicate | hasSubdivisions |
P747
|
FINISHED |
| Object |
Taijiang District
Taijiang District is a central urban district of Fuzhou in Fujian Province, China, known for its commercial activity and dense residential areas.
|
E595066
|
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: Taijiang District | Statement: [Fuzhou, hasSubdivisions, Taijiang District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taijiang District Context triple: [Fuzhou, hasSubdivisions, Taijiang District]
-
A.
Wuling District
Wuling District is the central urban district and administrative hub of Changde City in Hunan Province, China.
-
B.
Fengnan District
Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
C.
Yuetang District
Yuetang District is an urban administrative district of Xiangtan City in Hunan Province, China, known as one of its central built-up areas.
-
D.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
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: Taijiang District Triple: [Fuzhou, hasSubdivisions, Taijiang District]
Generated description
Taijiang District is a central urban district of Fuzhou in Fujian Province, China, known for its commercial activity and dense residential areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taijiang District Target entity description: Taijiang District is a central urban district of Fuzhou in Fujian Province, China, known for its commercial activity and dense residential areas.
-
A.
Wuling District
Wuling District is the central urban district and administrative hub of Changde City in Hunan Province, China.
-
B.
Fengnan District
Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
C.
Yuetang District
Yuetang District is an urban administrative district of Xiangtan City in Hunan Province, China, known as one of its central built-up areas.
-
D.
Xicheng District
Xicheng District is a central urban district of Beijing, China, known for its historic sites, government institutions, and cultural landmarks.
-
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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0346ac31c8190bbd28444f75da875 |
completed | March 22, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64b93ae1c8190a0207247dc93220b |
completed | March 27, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69c64d52cf8081908b797a68217a4341 |
completed | March 27, 2026, 9:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c64e2adf448190829c2a86c4e483eb |
completed | March 27, 2026, 9:30 a.m. |
Created at: March 22, 2026, 3:54 p.m.