Triple
T15397121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingotto station |
E368204
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Turin Metro |
E74302
|
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: Turin Metro | Statement: [Lingotto station, partOf, Turin Metro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turin Metro Context triple: [Lingotto station, partOf, Turin Metro]
-
A.
Turin Metro
chosen
The Turin Metro is a fully automated, driverless rapid transit system serving the city of Turin, Italy.
-
B.
Brescia Metro
Brescia Metro is a fully automated light metro system serving the city of Brescia in northern Italy.
-
C.
Milan Metro
The Milan Metro is the rapid transit system serving Milan, Italy, forming the backbone of the city’s public transportation network with multiple underground lines connecting central and suburban areas.
-
D.
Genoa Metro Line 1
Genoa Metro Line 1 is the primary light metro line serving the Italian city of Genoa, connecting key central and suburban areas through an underground rapid transit system.
-
E.
Minimetrò
Minimetrò is an automated, cable-driven people mover system that serves as a key component of Perugia’s urban public transportation network.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8c5d40819086622b70edcb6294 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff677ef27c81909fd160205b71ca55 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 3:19 a.m.