Triple
T13824363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Beijing Subway) |
E332211
|
entity |
| Predicate | servesStation |
P839
|
FINISHED |
| Object | Caishikou station |
E400429
|
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: Caishikou station | Statement: [Line 4 (Beijing Subway), servesStation, Caishikou station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caishikou station Context triple: [Line 4 (Beijing Subway), servesStation, Caishikou station]
-
A.
Caishikou station
chosen
Caishikou station is a Beijing Subway interchange station serving central Beijing, known for connecting Line 4 with other key routes near the historic Caishikou area.
-
B.
Jishuitan station
Jishuitan station is a subway station in Beijing that serves the busy Line 2 loop near the city’s northern central area.
-
C.
Tuqiao Station
Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
-
D.
Wudaokou station
Wudaokou station is a busy Beijing Subway stop in the Haidian District, known for serving a major university and tech hub area popular with students and young professionals.
-
E.
Xinzhuang Station
Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0285fb7c8190be4b90bdc0d6fa53 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda9009ce88190b77c8f02f38107e1 |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 9, 2026, 10:13 p.m.