Triple
T2708615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xuzhou |
E59803
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Xinyi
Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
|
E290943
|
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: Xinyi | Statement: [Xuzhou, hasSubdivision, Xinyi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xinyi Context triple: [Xuzhou, hasSubdivision, Xinyi]
-
A.
Xinyu
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
-
B.
Nantou
Nantou is a historic subdistrict in Shenzhen’s Nanshan District, known as the site of the old county seat and a preserved ancient town area.
-
C.
Tainan
Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
-
D.
Taoyuan City
Taoyuan City is a major municipality in northwestern Taiwan known for its rapidly growing urban areas, industrial zones, and proximity to Taiwan Taoyuan International Airport.
-
E.
Keelung
Keelung is a major port city in northeastern Taiwan known for its busy harbor, seafood markets, and coastal scenery.
- 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: Xinyi Triple: [Xuzhou, hasSubdivision, Xinyi]
Generated description
Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Xinyi Target entity description: Xinyi is a county-level city administered by Xuzhou in Jiangsu Province, eastern China.
-
A.
Xinyu
Xinyu is a prefecture-level industrial city located in central Jiangxi Province in southeastern China.
-
B.
Nantou
Nantou is a historic subdistrict in Shenzhen’s Nanshan District, known as the site of the old county seat and a preserved ancient town area.
-
C.
Tainan
Tainan is a historic city in southern Taiwan known for its well-preserved temples, traditional culture, and status as the island’s former capital.
-
D.
Taoyuan City
Taoyuan City is a major municipality in northwestern Taiwan known for its rapidly growing urban areas, industrial zones, and proximity to Taiwan Taoyuan International Airport.
-
E.
Keelung
Keelung is a major port city in northeastern Taiwan known for its busy harbor, seafood markets, and coastal scenery.
- 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda7542548190bbf6c947145f7f63 |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf7f99508190acfd00baec64b7e9 |
completed | March 10, 2026, 5:43 a.m. |
| NEDg | Description generation | batch_69afb02d8ff08190af2224c03b762c68 |
completed | March 10, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb0ae71888190ab0675b7897f1589 |
completed | March 10, 2026, 5:48 a.m. |
Created at: March 6, 2026, 9:55 p.m.