Triple
T10499230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dongcheng District, Beijing |
E247622
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Dongdan |
E251449
|
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: Dongdan | Statement: [Dongcheng District, Beijing, contains, Dongdan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dongdan Context triple: [Dongcheng District, Beijing, contains, Dongdan]
-
A.
Dongdan
chosen
Dongdan is a central commercial and transportation hub in Beijing known for its shopping streets, offices, and busy intersections.
-
B.
Dongsi
Dongsi is a historic neighborhood and street-crossroads area in central Beijing known for its traditional hutong lanes and long-standing commercial streets.
-
C.
Dongmen
Dongmen is a key Taipei Metro station in central Taipei that serves as a busy transfer point between multiple subway lines and nearby commercial and residential areas.
-
D.
Chongwenmen
Chongwenmen is a historic gate area in central Beijing that once formed part of the old city wall and now serves as a major commercial and transportation hub.
-
E.
Chaoyang
Chaoyang is a prefecture-level city in western Liaoning Province, China, known for its historical sites and role as a regional transportation and agricultural center.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5098e45ec8190a02b981a06786909 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d933d4b63081909ad297038fb74bed |
completed | April 10, 2026, 5:31 p.m. |
Created at: April 6, 2026, 12:25 p.m.