Triple
T15735924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huludao |
E381470
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Lianshan District
Lianshan District is an urban administrative district of Huludao City in Liaoning Province, northeastern China.
|
E1325234
|
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: Lianshan District | Statement: [Huludao, hasSubdivision, Lianshan District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lianshan District Context triple: [Huludao, hasSubdivision, Lianshan District]
-
A.
Mingshan District
Mingshan District is an urban administrative district of the city of Benxi in Liaoning Province, northeastern China.
-
B.
Jiancaoping District
Jiancaoping District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its industrial development and residential areas.
-
C.
Fengnan District
Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
D.
Shunqing District
Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
-
E.
Yushui District
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
- 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: Lianshan District Triple: [Huludao, hasSubdivision, Lianshan District]
Generated description
Lianshan District is an urban administrative district of Huludao City in Liaoning Province, northeastern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lianshan District Target entity description: Lianshan District is an urban administrative district of Huludao City in Liaoning Province, northeastern China.
-
A.
Mingshan District
Mingshan District is an urban administrative district of the city of Benxi in Liaoning Province, northeastern China.
-
B.
Jiancaoping District
Jiancaoping District is an urban district of Taiyuan, the capital city of Shanxi Province in northern China, known for its industrial development and residential areas.
-
C.
Fengnan District
Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
D.
Shunqing District
Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
-
E.
Yushui District
Yushui District is the central urban district and administrative seat of Xinyu, a prefecture-level city in Jiangxi Province, China.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd586a88190aa1b1b88368d386f |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a040fc34f4c8190a1ae536e544b2543 |
completed | May 13, 2026, 5:44 a.m. |
| NEDg | Description generation | batch_6a04123430308190af22a11b2151c8b8 |
completed | May 13, 2026, 5:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a04131eb4988190af4024bfcad648bc |
completed | May 13, 2026, 5:58 a.m. |
Created at: April 10, 2026, 4:46 a.m.