Triple
T12707873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yingkou |
E303634
|
entity |
| Predicate | hasCountyLevelCity |
P27799
|
FINISHED |
| Object | Dashiqiao |
E1004175
|
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: Dashiqiao | Statement: [Yingkou, hasCountyLevelCity, Dashiqiao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dashiqiao Context triple: [Yingkou, hasCountyLevelCity, Dashiqiao]
-
A.
Dashiqiao
chosen
Dashiqiao is a county-level city in Liaoning Province, China, known for its magnesite resources and industrial production.
-
B.
Beixinqiao
Beixinqiao is a neighborhood and subway station area in central Beijing known for its traditional hutong streets, local eateries, and convenient access to several key city districts.
-
C.
Hufangqiao
Hufangqiao is a subway station in Beijing, China, serving passengers on the city's extensive metro network.
-
D.
Tangqiao
Tangqiao is a Shanghai Metro station located in the city's central area, serving passengers on the circular Line 4 route.
-
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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9620663e881908d367170ed6d2c81 |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b8a79488190aaf95d4f2e20a7bc |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:23 p.m.