Triple
T13824459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Beijing Subway) |
E332214
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Xidan station |
E69578
|
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: Xidan station | Statement: [Line 1 (Beijing Subway), hasStation, Xidan station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xidan station Context triple: [Line 1 (Beijing Subway), hasStation, Xidan station]
-
A.
Xidan station
chosen
Xidan station is a major interchange stop on the Beijing Subway serving the busy commercial and shopping district of Xidan in central Beijing.
-
B.
Shichahai station
Shichahai station is an underground metro stop on the Beijing Subway serving the historic Shichahai scenic area near central Beijing.
-
C.
Jishuitan station
Jishuitan station is a subway station in Beijing that serves the busy Line 2 loop near the city’s northern central area.
-
D.
Caishikou station
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.
-
E.
Tenjin Station
Tenjin Station is a major underground railway and commercial hub in central Fukuoka, Japan, serving as one of the city's busiest transit and shopping areas.
- 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_69fbc31a91608190a80a69be38ac7f71 |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:13 p.m.