Triple
T5599196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jilin Province |
E147072
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Baishan
Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
|
E551492
|
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: Baishan | Statement: [Jilin Province, containsCity, Baishan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baishan Context triple: [Jilin Province, containsCity, Baishan]
-
A.
Shuangyashan
Shuangyashan is a coal-mining and industrial city in northeastern China known for its energy resources and heavy industry.
-
B.
Songyuan
Songyuan is a prefecture-level city in northwestern Jilin Province, China, known as an important regional hub for agriculture, petrochemicals, and transportation.
-
C.
Sudak
Sudak is a historic resort town on the southeastern coast of Crimea, known for its well-preserved medieval Genoese fortress and scenic Black Sea beaches.
-
D.
Hegang
Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
-
E.
Yangsan
Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
- 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: Baishan Triple: [Jilin Province, containsCity, Baishan]
Generated description
Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baishan Target entity description: Baishan is a prefecture-level city in southeastern Jilin Province, China, known for its mountainous terrain, forest resources, and proximity to Changbai Mountain.
-
A.
Shuangyashan
Shuangyashan is a coal-mining and industrial city in northeastern China known for its energy resources and heavy industry.
-
B.
Songyuan
Songyuan is a prefecture-level city in northwestern Jilin Province, China, known as an important regional hub for agriculture, petrochemicals, and transportation.
-
C.
Sudak
Sudak is a historic resort town on the southeastern coast of Crimea, known for its well-preserved medieval Genoese fortress and scenic Black Sea beaches.
-
D.
Hegang
Hegang is a coal-mining city in northeastern Heilongjiang Province, China, located near the Russian border along the Amur River region.
-
E.
Yangsan
Yangsan is a city in South Gyeongsang Province, South Korea, known as a growing residential and educational hub near Busan.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020d82870819087f9591b5a1021ce |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a142ae8c8190a8c4a02bb3f69ff2 |
completed | March 23, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69c0a1faf7d48190ad2d5f43ef37da82 |
completed | March 23, 2026, 2:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a2e17cd88190a54f5166fe5c654a |
completed | March 23, 2026, 2:18 a.m. |
Created at: March 22, 2026, 3:38 p.m.