Triple
T14767100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | western Beijing |
E347024
|
entity |
| Predicate | hasNotableArea |
P494
|
FINISHED |
| Object | Wudaokou |
E410697
|
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: Wudaokou | Statement: [western Beijing, hasNotableArea, Wudaokou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wudaokou Context triple: [western Beijing, hasNotableArea, Wudaokou]
-
A.
Wudaokou
chosen
Wudaokou is a bustling neighborhood in Beijing known for its universities, tech companies, and vibrant student nightlife.
-
B.
Lüshunkou
Lüshunkou is a strategically important port city at the tip of the Liaodong Peninsula in northeastern China, historically known as Port Arthur and the site of major naval and military conflicts.
-
C.
Caishikou
Caishikou is a subway station in central Beijing that serves as an important stop on the city’s urban rail network.
-
D.
Wafangdian
Wafangdian is a county-level city in Liaoning Province, China, known for its bearing industry and as an important satellite city of Dalian.
-
E.
Jinqiao
Jinqiao is a subdistrict in Shanghai’s Pudong New Area known for its residential communities and growing commercial and industrial zones.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f576c881909da70627f5897c94 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf68d94819093567bc630f67b60 |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:30 a.m.