Triple
T21438557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siping |
E528877
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Tiedong District
Tiedong District is an urban administrative district of the prefecture-level city of Siping in Jilin Province, northeastern China.
|
E1484968
|
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: Tiedong District | Statement: [Siping, hasSubdivision, Tiedong District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiedong District Context triple: [Siping, hasSubdivision, Tiedong District]
-
A.
Tiedong District
Tiedong District is an urban administrative district of Anshan City in Liaoning Province, northeastern China.
-
B.
Bagongshan District
Bagongshan District is an urban administrative district of Huainan City in Anhui Province, China, known for its coal resources and industrial development.
-
C.
Pinglin District
Pinglin District is a rural, mountainous area in southeastern New Taipei City, Taiwan, best known for its tea production and scenic natural landscapes.
-
D.
Hongta District
Hongta District is the central urban district and administrative seat of Yuxi City in Yunnan Province, China.
-
E.
Beimen District
Beimen District is a coastal district in Tainan, Taiwan, known for its historic salt fields, wetlands, and traditional temples.
- 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: Tiedong District Triple: [Siping, hasSubdivision, Tiedong District]
Generated description
Tiedong District is an urban administrative district of the prefecture-level city of Siping in Jilin Province, northeastern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiedong District Target entity description: Tiedong District is an urban administrative district of the prefecture-level city of Siping in Jilin Province, northeastern China.
-
A.
Tiedong District
Tiedong District is an urban administrative district of Anshan City in Liaoning Province, northeastern China.
-
B.
Bagongshan District
Bagongshan District is an urban administrative district of Huainan City in Anhui Province, China, known for its coal resources and industrial development.
-
C.
Pinglin District
Pinglin District is a rural, mountainous area in southeastern New Taipei City, Taiwan, best known for its tea production and scenic natural landscapes.
-
D.
Hongta District
Hongta District is the central urban district and administrative seat of Yuxi City in Yunnan Province, China.
-
E.
Beimen District
Beimen District is a coastal district in Tainan, Taiwan, known for its historic salt fields, wetlands, and traditional temples.
- 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_69e0c4569fa081908101baa24f8745db |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee8140a1fc8190bedf297cfc4d4841 |
completed | April 26, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c8ff456481908092ae0af1297aab |
completed | May 17, 2026, 1:56 p.m. |
| NEDg | Description generation | batch_6a09c99200a88190ad13565044dfcac0 |
completed | May 17, 2026, 1:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09ca47743081908cf7f9211eeedcc6 |
completed | May 17, 2026, 2:01 p.m. |
Created at: April 16, 2026, 6:04 p.m.