Triple
T12341270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tacuba metro station |
E294230
|
entity |
| Predicate | hasMetroLine |
P17559
|
FINISHED |
| Object | Line 7 |
E873075
|
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: Line 7 | Statement: [Tacuba metro station, hasMetroLine, Line 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 7 Context triple: [Tacuba metro station, hasMetroLine, Line 7]
-
A.
Line 7
Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
-
B.
Line 7
Line 7 is a major rapid transit route of the Shanghai Metro that runs in a roughly north–south direction, connecting several key residential, commercial, and cultural areas across the city.
-
C.
Line 7
Line 7 is a Culver CityBus route in the Los Angeles area that provides local public transit service connecting key neighborhoods and transit hubs.
-
D.
Line 7
Line 7 is a line of the Moscow Metro system, known as the Tagansko-Krasnopresnenskaya Line, serving various districts across the city.
-
E.
Line 7
chosen
Line 7 is one of the main lines of the Mexico City Metro system, running across the city on a predominantly underground route and connecting several key neighborhoods and transfer stations.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7758dc8190bbc6a9ad00b01dce |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aaa1d548190be065412aab70385 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.