Triple
T2159994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Line 3 |
E47977
|
entity |
| Predicate | connectsWithLine |
P845
|
FINISHED |
| Object | Line 6 |
unclear NED1
|
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 6 | Statement: [Metro Line 3, connectsWithLine, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Metro Line 3, connectsWithLine, Line 6]
-
A.
Line 6
Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
-
B.
Line 6
Line 6 is a modern, fully automated metro line in the Santiago Metro system in Chile, known for its driverless trains and advanced safety features.
-
C.
Line 6
Line 6 is a route of the Mexico City Metro system that runs east–west across the northern part of the city, connecting several residential and commercial areas.
-
D.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
-
E.
Line 6
Line 6 is a rapid transit line of the Shanghai Metro system serving several districts along the city’s eastern side.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8894d481908eda9363fd36fea6 |
completed | March 7, 2026, 5:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58e9ceb08190871ff9c57ece23c0 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:45 p.m.