Triple
T13971454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boissière |
E336072
|
entity |
| Predicate | hasRollingStock |
P1305
|
FINISHED |
| Object | MF 77 |
E207261
|
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: MF 77 | Statement: [Boissière, hasRollingStock, MF 77]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MF 77 Context triple: [Boissière, hasRollingStock, MF 77]
-
A.
MF 77
chosen
MF 77 is a steel-wheeled electric multiple unit train used on several lines of the Paris Métro, introduced in the late 1970s to modernize the network’s rolling stock.
-
B.
MF 67
MF 67 is a class of steel-wheeled electric multiple unit trains that have long served as a primary rolling stock type on the Paris Métro.
-
C.
M-77
M-77 is a state highway in Michigan, United States, running north–south through the eastern Upper Peninsula.
-
D.
MF 88
MF 88 is a type of rubber-tyred electric multiple unit train used on the Paris Métro, notable for its experimental design and limited deployment.
-
E.
MF 19
MF 19 is a planned new generation of Paris Métro rubber-tyred rolling stock intended to replace older MF-series trains on several lines.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8eae40819080dd4bd25c73b6d6 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1dc838c8190bbcfefd69ea29965 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.