Triple
T8573097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayannur |
E202975
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Linhe District
Linhe District is the urban administrative center of Bayannur in Inner Mongolia, China, serving as its political and economic hub.
|
E763473
|
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: Linhe District | Statement: [Bayannur, capital, Linhe District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linhe District Context triple: [Bayannur, capital, Linhe District]
-
A.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
B.
Dongsheng District
Dongsheng District is the central urban district and administrative hub of Ordos City in Inner Mongolia, China.
-
C.
Wanbailin District
Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Qilihe District
Qilihe District is an urban administrative district of Lanzhou, the capital city of Gansu Province in northwestern China.
-
E.
Hekou District
Hekou District is an urban administrative district of Dongying City in Shandong Province, China, known for its role in the development of the Shengli oilfield and the Yellow River Delta region.
- 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: Linhe District Triple: [Bayannur, capital, Linhe District]
Generated description
Linhe District is the urban administrative center of Bayannur in Inner Mongolia, China, serving as its political and economic hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Linhe District Target entity description: Linhe District is the urban administrative center of Bayannur in Inner Mongolia, China, serving as its political and economic hub.
-
A.
Hecheng District
Hecheng District is the central urban district and administrative seat of Huaihua in Hunan Province, China.
-
B.
Dongsheng District
Dongsheng District is the central urban district and administrative hub of Ordos City in Inner Mongolia, China.
-
C.
Wanbailin District
Wanbailin District is an urban administrative district of Taiyuan, the capital city of Shanxi Province in northern China.
-
D.
Qilihe District
Qilihe District is an urban administrative district of Lanzhou, the capital city of Gansu Province in northwestern China.
-
E.
Hekou District
Hekou District is an urban administrative district of Dongying City in Shandong Province, China, known for its role in the development of the Shengli oilfield and the Yellow River Delta region.
- 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_69ca8328ebe481909a8c038fa79959b4 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea458c1081908e79bee2cbf97207 |
completed | March 31, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf9ffe17e481908516d2f526d60684 |
completed | April 3, 2026, 11:09 a.m. |
| NEDg | Description generation | batch_69cfa3ca78848190a8e44a2419d1eccd |
completed | April 3, 2026, 11:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa4203f7c819084d27a53928812cd |
completed | April 3, 2026, 11:27 a.m. |
Created at: March 30, 2026, 6:21 p.m.