Triple
T15427472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xiang Jingyu |
E369548
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Wuhan |
E1680
|
NE FINISHED |
How this triple was built (2 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: Wuhan | Statement: [Xiang Jingyu, placeOfDeath, Wuhan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wuhan Context triple: [Xiang Jingyu, placeOfDeath, Wuhan]
-
A.
Wuhan
chosen
Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
-
B.
Hankou
Hankou is a historic commercial and port city that now forms one of the three main towns of modern Wuhan in central China.
-
C.
Huangshi
Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
-
D.
Chongqing
Chongqing is a vast inland metropolis in southwestern China known for its steep hilly terrain, spicy hotpot cuisine, and role as a major industrial and transportation hub along the upper Yangtze River.
-
E.
Guangzhou
Guangzhou is a major port city in southern China and the capital of Guangdong Province, known as a key commercial and manufacturing hub in the Pearl River Delta.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ec31f4881908b26ff7c381d7bc9 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cf5d788819086a94af42c2ec21a |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:20 a.m.