Triple
T2631964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baquedano |
E59654
|
entity |
| Predicate | isInterchangeBetween |
P21487
|
FINISHED |
| Object | Line 3 and Line 5 |
E218789
|
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 3 and Line 5 | Statement: [Baquedano, isInterchangeBetween, Line 3 and Line 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 3 and Line 5 Context triple: [Baquedano, isInterchangeBetween, Line 3 and Line 5]
-
A.
Line 3
Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
-
B.
Line 3
Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
C.
Line 3
chosen
Line 3 is one of the main lines of the Mexico City Metro system, running in a generally north–south direction and serving several key residential and commercial areas.
-
D.
Line 3
Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
-
E.
Line 3
Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8c6e540819087c7f92432b27b0f |
completed | March 7, 2026, 7:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af90a7021081909f81c4ddb48fa00c |
completed | March 10, 2026, 3:31 a.m. |
Created at: March 6, 2026, 9:50 p.m.