Triple
T11379749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tacubaya |
E269561
|
entity |
| Predicate | metroLines |
P17559
|
FINISHED |
| Object | Line 7 |
E44446
|
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: [Tacubaya, metroLines, Line 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 7 Context triple: [Tacubaya, metroLines, Line 7]
-
A.
Line 7
chosen
Line 7 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
B.
Line 7
Line 7 is an east–west rapid transit line of the Beijing Subway serving several central and southwestern districts of Beijing.
-
C.
Line 7
Line 7 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou and its surrounding areas.
-
D.
Line 7
Line 7 is one of the main lines of the Tehran Metro rapid transit network, serving various districts of Iran’s capital city.
-
E.
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.
- 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.