Triple
T13964052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linfen |
E335875
|
entity |
| Predicate | hasSeat |
P3522
|
FINISHED |
| Object |
Yaodu District
Yaodu District is the central urban district and administrative heart of Linfen City in Shanxi Province, China.
|
E1072541
|
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: Yaodu District | Statement: [Linfen, hasSeat, Yaodu District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yaodu District Context triple: [Linfen, hasSeat, Yaodu District]
-
A.
Diecai District
Diecai District is an urban district of Guilin in Guangxi, China, known for its scenic karst landscapes and role as part of the city’s core administrative area.
-
B.
Yunlong District
Yunlong District is an urban administrative district and central area of Xuzhou City in Jiangsu Province, China.
-
C.
Wanbailin District
Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Fengrun District
Fengrun District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
E.
Dadu District
Dadu District is an administrative district in the Sindh province of Pakistan, known for its historical archaeological sites and proximity to the Indus River.
- 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: Yaodu District Triple: [Linfen, hasSeat, Yaodu District]
Generated description
Yaodu District is the central urban district and administrative heart of Linfen City in Shanxi Province, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yaodu District Target entity description: Yaodu District is the central urban district and administrative heart of Linfen City in Shanxi Province, China.
-
A.
Diecai District
Diecai District is an urban district of Guilin in Guangxi, China, known for its scenic karst landscapes and role as part of the city’s core administrative area.
-
B.
Yunlong District
Yunlong District is an urban administrative district and central area of Xuzhou City in Jiangsu Province, China.
-
C.
Wanbailin District
Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Fengrun District
Fengrun District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
E.
Dadu District
Dadu District is an administrative district in the Sindh province of Pakistan, known for its historical archaeological sites and proximity to the Indus River.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e7e24f08190ba939a8044860033 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1d890d48190affd194b2439c271 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba7149cf08190942cc9b1f7f208f0 |
completed | May 6, 2026, 8:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba8fe11c881908662d8e8e1720ea4 |
completed | May 6, 2026, 8:47 p.m. |
Created at: April 9, 2026, 10:18 p.m.