Triple
T8883734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 4 (Paris Métro) |
E211472
|
entity |
| Predicate | rollingStock |
P1305
|
FINISHED |
| Object | MP 89 trains |
E199955
|
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: MP 89 trains | Statement: [Line 4 (Paris Métro), rollingStock, MP 89 trains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MP 89 trains Context triple: [Line 4 (Paris Métro), rollingStock, MP 89 trains]
-
A.
MP 89 trains
chosen
MP 89 trains are a class of rubber-tyred, automated-capable Paris Métro rolling stock known for their modern design and use on several key lines of the network.
-
B.
MP-68 trains
MP-68 trains are a class of rubber-tyred metro rolling stock that have operated on Mexico City’s Metro system since the late 1960s.
-
C.
MP 05 trains
MP 05 trains are modern, rubber-tyred, automated metro trainsets used on several lines of the Paris Métro.
-
D.
MP 14 trains
MP 14 trains are a modern generation of rubber-tyred Paris Métro trains designed for automated operation, improved energy efficiency, and enhanced passenger comfort.
-
E.
Pesa trains
Pesa trains are modern electric multiple units manufactured by the Polish company Pesa, used as part of the rolling stock on systems such as the Sofia Metro.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc616b2d988190b923ef1e33aab787 |
completed | April 1, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfabd254148190b5ea3d308fe96851 |
completed | April 3, 2026, noon |
Created at: March 30, 2026, 6:53 p.m.