Triple
T13824468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Beijing Subway) |
E332214
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Sihui station |
E72671
|
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: Sihui station | Statement: [Line 1 (Beijing Subway), hasStation, Sihui station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sihui station Context triple: [Line 1 (Beijing Subway), hasStation, Sihui station]
-
A.
Sihui station
chosen
Sihui station is a Beijing Subway interchange station serving as a key transfer point between major urban rail lines in the city.
-
B.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
-
C.
Jiantan Station
Jiantan Station is a Taipei Metro station in Taiwan that serves as a major access point for visitors to the popular Shilin Night Market.
-
D.
Lijiao Station
Lijiao Station is an interchange station on the Guangzhou Metro system in Guangzhou, China, serving as a local transit hub for passengers in its surrounding urban area.
-
E.
Baishizhou station
Baishizhou station is a metro station in Shenzhen, China, serving the densely populated Baishizhou area and nearby attractions such as Window of the World.
- 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_69f7c0e966c48190abe109d44300014a |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 10:13 p.m.