Triple
T11379750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tacubaya |
E269561
|
entity |
| Predicate | metroLines |
P17559
|
FINISHED |
| Object | Line 9 |
E110193
|
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 9 | Statement: [Tacubaya, metroLines, Line 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 9 Context triple: [Tacubaya, metroLines, Line 9]
-
A.
Line 9
Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
-
B.
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.
-
C.
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.
-
D.
Line 9
chosen
Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
-
E.
Line 9
Line 9 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving several key districts in the city.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc30f5d48190bb273df4c9e583a9 |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e556a10f988190b173dc4880a8c6c6 |
completed | April 19, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:34 p.m.