Triple
T7615573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenghua |
E172352
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Xikou Town |
E180956
|
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: Xikou Town | Statement: [Fenghua, contains, Xikou Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xikou Town Context triple: [Fenghua, contains, Xikou Town]
-
A.
Xikou Town
chosen
Xikou Town is a historic town in Fenghua District, Ningbo, Zhejiang Province, best known as the hometown of Chiang Kai-shek and a popular cultural and tourist destination.
-
B.
Gaotangling town
Gaotangling town is an urban township that serves as the main commercial and administrative center of Wangcheng County in Hunan Province, China.
-
C.
Gaojing Town
Gaojing Town is an administrative town located within Baoshan District in the northern part of Shanghai, China.
-
D.
Luojing Town
Luojing Town is a suburban township-level division of Shanghai, China, situated within the municipality’s northern Baoshan District.
-
E.
Miaohang Town
Miaohang Town is a suburban township-level division in the northern part of Shanghai, China, known for its mix of residential, industrial, and developing urban areas.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa4569c88190b2968403a24e7882 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c87097d3a48190b337ff6906847d4e |
completed | March 29, 2026, 12:21 a.m. |
Created at: March 27, 2026, 3:55 p.m.