Triple
T19485133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon Metro |
E487491
|
entity |
| Predicate | hasRollingStock |
P1305
|
FINISHED |
| Object | MPL 16 |
—
|
NE NERFINISHED |
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: MPL 16 | Statement: [Lyon Metro, hasRollingStock, MPL 16]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MPL 16 Context triple: [Lyon Metro, hasRollingStock, MPL 16]
-
A.
MPL 16
chosen
MPL 16 is a modern automated rubber-tyred metro train used on Lyon’s Line B as part of the network’s upgraded driverless rolling stock.
-
B.
MPL 85
MPL 85 is a type of rubber-tyred, automated metro train used on Lyon’s Line D.
-
C.
MPL
MPL is the National Rail station code for Marple railway station in Greater Manchester, England.
-
D.
MPL
MPL (Mozilla Public License) is a free and open-source software license created by Mozilla that allows code to be shared and modified while requiring that changes to MPL-covered files remain publicly available.
-
E.
MPL
MPL is the IATA airport code for Montpellier-Méditerranée Airport, serving the city of Montpellier in southern France.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343dcc748190b0df816e6ab4cafb |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.