Triple
T4109068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Métro Line 13 |
E88523
|
entity |
| Predicate | rollingStock |
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: [Paris Métro Line 13, rollingStock, MF 77]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MF 77 Context triple: [Paris Métro Line 13, rollingStock, 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.
M-97
M-97 is a state highway in Michigan that serves as a key transportation route through the Detroit metropolitan area, including Warren.
-
E.
MR-73
MR-73 is a class of rubber-tired electric multiple unit trains used on the Montreal Metro system.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01da2b88819088a45401c0ec743a |
completed | March 9, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b850d588190a0fc4b784bc7ca4f |
completed | March 14, 2026, 2:07 p.m. |
Created at: March 9, 2026, 3:40 p.m.