Triple
T23259651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Express Bus Terminal Station |
E581967
|
entity |
| Predicate | hasSubwayLine |
P522
|
FINISHED |
| Object | Line 9 |
—
|
NE NERFINISHED |
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: Line 9 | Statement: [Express Bus Terminal Station, hasSubwayLine, Line 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 9 Context triple: [Express Bus Terminal Station, hasSubwayLine, Line 9]
-
A.
Line 9
Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
-
B.
Line 9
Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
-
C.
Line 9
Line 9 is a major Barcelona Metro line designed as a long, partially automated route connecting key suburban and airport areas with the wider metropolitan network.
-
D.
Line 9
chosen
Line 9 is a rapid transit route within the STC Metro system, serving as one of its numbered urban rail lines.
-
E.
Line 9
Line 9 is a rapid transit line of the Chongqing Metro system in Chongqing, China, serving as part of the city's expanding urban rail network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c7ec148190b01fd215a0c1daa1 |
completed | April 29, 2026, 5:19 a.m. |
Created at: April 17, 2026, 4:11 p.m.