Triple
T18582685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tangshan Prefecture-level City |
E454154
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Fengnan District |
—
|
NE NERFINISHED |
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: Fengnan District | Statement: [Tangshan Prefecture-level City, hasSubdivision, Fengnan District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fengnan District Context triple: [Tangshan Prefecture-level City, hasSubdivision, Fengnan District]
-
A.
Fengnan District
chosen
Fengnan District is an administrative district under the jurisdiction of the prefecture-level city of Tangshan in Hebei Province, China.
-
B.
Shunqing District
Shunqing District is the central urban district and administrative heart of Nanchong City in Sichuan Province, China.
-
C.
Yuhua District
Yuhua District is an urban administrative district of Changsha, the capital city of Hunan Province in south-central China.
-
D.
Jianhua District
Jianhua District is a central urban district of Qiqihar City in Heilongjiang Province, northeastern China.
-
E.
Fangzi District
Fangzi District is an urban administrative district within the prefecture-level city of Weifang in Shandong Province, eastern China.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e543d10b1c8190a401df810b7290c9 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 11:44 a.m.