Triple
T11870693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Line 9 |
E282398
|
entity |
| Predicate | connectsWithLine |
P845
|
FINISHED |
| Object | Line A |
E100153
|
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 A | Statement: [Metro Line 9, connectsWithLine, Line A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line A Context triple: [Metro Line 9, connectsWithLine, Line A]
-
A.
Line A
chosen
Line A is a line of the Mexico City Metro system that serves the eastern part of the metropolitan area, connecting central Mexico City with several suburban municipalities.
-
B.
Line A
Line A is the main north–south rapid transit line of the Medellín Metro system in Colombia, serving as its busiest and most central corridor.
-
C.
Line A
Line A is the primary route of the Bilbao tram system, serving key areas of the city with modern light rail service.
-
D.
Line A
Line A is one of the main lines of the Prague Metro, running east–west through the city and serving several central and residential districts.
-
E.
Line A
Line A is one of the main tram lines serving the city of Reims, France, providing urban public transportation across key 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8be15fb2481908f514781ce2c617f |
completed | April 10, 2026, 9:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281b0969c8190a8c0a01ca292cc84 |
completed | April 29, 2026, 10:09 p.m. |
Created at: April 8, 2026, 9:43 p.m.