Triple
T18795407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dameisha |
E459620
|
entity |
| Predicate | nearTo |
P350
|
FINISHED |
| Object | Xiaomeisha |
—
|
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: Xiaomeisha | Statement: [Dameisha, nearTo, Xiaomeisha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xiaomeisha Context triple: [Dameisha, nearTo, Xiaomeisha]
-
A.
Xiaomeisha
chosen
Xiaomeisha is a popular coastal resort area in Shenzhen, China, known for its sandy beaches, seaside recreation, and tourist attractions.
-
B.
Fengxia
Fengxia is a central character in Yu Hua's novel "To Live," known as the mute daughter whose quiet resilience and tragic fate embody the suffering and endurance of an ordinary Chinese family through decades of political and social upheaval.
-
C.
Zhuzihu
Zhuzihu is a scenic valley area in Taipei’s Yangmingshan National Park, best known for its cool-climate agriculture and seasonal calla lily fields.
-
D.
Xiluoyuan
Xiluoyuan is a residential neighborhood and subdistrict located in Beijing’s Fengtai District.
-
E.
Xinzhu
Xinzhu is a city that serves as a sister city to Bielefeld, Germany, and is likely a regional urban center with cultural and economic significance.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a01dbb308190bbbbd5a18e26451e |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 10, 2026, 11:53 a.m.