Triple
T8919337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikumen |
E212370
|
entity |
| Predicate | notableExample |
P1503
|
FINISHED |
| Object | Xintiandi |
E37624
|
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: Xintiandi | Statement: [Shikumen, notableExample, Xintiandi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xintiandi Context triple: [Shikumen, notableExample, Xintiandi]
-
A.
Xintiandi
chosen
Xintiandi is a fashionable, pedestrian-only district in central Shanghai known for its upscale shopping, dining, nightlife, and preserved Shikumen-style architecture.
-
B.
Tianzifang
Tianzifang is a popular arts and crafts enclave in Shanghai known for its narrow alleyways, renovated traditional shikumen buildings, and vibrant mix of boutiques, galleries, cafés, and bars.
-
C.
Sanxiantai
Sanxiantai is a scenic coastal area and small offshore island in eastern Taiwan, famous for its arched footbridge, unique rock formations, and rich marine ecology.
-
D.
Xiluoyuan
Xiluoyuan is a residential neighborhood and subdistrict located in Beijing’s Fengtai District.
-
E.
Xiaomeisha
Xiaomeisha is a popular coastal resort area in Shenzhen, China, known for its sandy beaches, seaside recreation, and tourist attractions.
- 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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6613639881909090d060f388a865 |
completed | April 1, 2026, 12:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfba49d65c8190b9d9908822198cc0 |
completed | April 3, 2026, 1:02 p.m. |
Created at: March 30, 2026, 6:56 p.m.