Triple
T7718189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zibo |
E174939
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Linzi District
Linzi District is an urban district of Zibo in Shandong Province, China, historically known as the ancient capital of the State of Qi.
|
E691779
|
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: Linzi District | Statement: [Zibo, contains, Linzi District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linzi District Context triple: [Zibo, contains, Linzi District]
-
A.
Xiejiaji District
Xiejiaji District is an urban administrative district of Huainan City in Anhui Province, China, known for its role in the region’s coal-based industrial economy.
-
B.
Neihu District
Neihu District is a suburban and technology-focused district in northeastern Taipei, Taiwan, known for its science parks, residential communities, and natural scenery.
-
C.
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
D.
Dawan District
Dawan District is an administrative district in Klungkung Regency on the island of Bali, Indonesia.
-
E.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong 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: Linzi District Triple: [Zibo, contains, Linzi District]
Generated description
Linzi District is an urban district of Zibo in Shandong Province, China, historically known as the ancient capital of the State of Qi.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Linzi District Target entity description: Linzi District is an urban district of Zibo in Shandong Province, China, historically known as the ancient capital of the State of Qi.
-
A.
Xiejiaji District
Xiejiaji District is an urban administrative district of Huainan City in Anhui Province, China, known for its role in the region’s coal-based industrial economy.
-
B.
Neihu District
Neihu District is a suburban and technology-focused district in northeastern Taipei, Taiwan, known for its science parks, residential communities, and natural scenery.
-
C.
Xialu District
Xialu District is an urban administrative district of the prefecture-level city of Huangshi in Hubei Province, China.
-
D.
Dawan District
Dawan District is an administrative district in Klungkung Regency on the island of Bali, Indonesia.
-
E.
Zhifu District
Zhifu District is the central urban district and administrative, commercial, and cultural core of Yantai in Shandong 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ceb23481909600f876023dde92 |
completed | March 27, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9a9ca03ec8190859d9728fef39d24 |
completed | March 29, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69c9aa8767448190a98c4ff7c5452a2a |
completed | March 29, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c9aabb80108190b12939eecab7077d |
completed | March 29, 2026, 10:42 p.m. |
Created at: March 27, 2026, 4:05 p.m.