Triple
T16930695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wudaokou |
E410697
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Tsinghua East Road |
E1222208
|
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: Tsinghua East Road | Statement: [Wudaokou, near, Tsinghua East Road]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tsinghua East Road Context triple: [Wudaokou, near, Tsinghua East Road]
-
A.
Heping East Road
Heping East Road is a major thoroughfare in Taipei, Taiwan, known for its busy traffic, commercial activity, and proximity to several universities and metro stations.
-
B.
Damuqiao Road
Damuqiao Road is a Shanghai Metro station and major transit point located in the central area of Shanghai, China.
-
C.
Changle Road
Changle Road is a historic, tree-lined street in Shanghai known for its European-style architecture, boutiques, and cafés dating back to the city’s colonial era.
-
D.
Zhichun Road
chosen
Zhichun Road is a major thoroughfare in Beijing, China, known for its location in the city’s technology and education district near several universities and tech companies.
-
E.
Tianhe Road
Tianhe Road is a major commercial and traffic artery in Guangzhou’s Tianhe District, lined with shopping centers, offices, and urban amenities.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf248c6c81908fbf4d49e5381f08 |
completed | April 18, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfdeb7a88190aac21a8645607dc8 |
completed | May 10, 2026, 6:35 p.m. |
Created at: April 10, 2026, 5:30 a.m.