Triple
T17830596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanhua District |
E445242
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Ximending |
—
|
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: Ximending | Statement: [Wanhua District, contains, Ximending]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ximending Context triple: [Wanhua District, contains, Ximending]
-
A.
Ximending
chosen
Ximending is a bustling shopping and entertainment district in Taipei known for its youth culture, street performances, and vibrant nightlife.
-
B.
Xiadu
Xiadu was an ancient Chinese city that served as a major political and cultural center of the Warring States–period Yan kingdom.
-
C.
Xiaojinmen
Xiaojinmen is a small outlying island of Kinmen County, Taiwan, located near the coast of mainland China and known for its military history and strategic position in the Taiwan Strait.
-
D.
Zhiyan
Zhiyan was an influential Chinese Buddhist monk and early Huayan school patriarch whose teachings shaped the thought of later Korean monk Uisang.
-
E.
Xintiandi
Xintiandi is a fashionable, pedestrian-only district in central Shanghai known for its upscale shopping, dining, nightlife, and preserved Shikumen-style architecture.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48917c4d88190b919a4b75aed011c |
completed | April 19, 2026, 7:49 a.m. |
Created at: April 10, 2026, 10:15 a.m.