Triple
T19054263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Green Line (Montreal Metro) |
E466349
|
entity |
| Predicate | operatedBy |
P86
|
FINISHED |
| Object | STM |
—
|
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: STM | Statement: [Green Line (Montreal Metro), operatedBy, STM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: STM Context triple: [Green Line (Montreal Metro), operatedBy, STM]
-
A.
STM
chosen
STM is the public transit agency serving the city of Montreal, operating its bus and metro networks.
-
B.
STM
STM is the station code for Smithtown station, a Long Island Rail Road commuter rail stop in Smithtown, New York.
-
C.
STM
STM is the stock ticker symbol for STMicroelectronics, a major global semiconductor manufacturer.
-
D.
STM
STM is the Finnish Ministry of Social Affairs and Health, the government body responsible for national social welfare and health policy in Finland.
-
E.
STA
STA is the vehicle registration code for the district of Starnberg in Bavaria, Germany.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5dc049f64819093ae9fda26a49bd2 |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 10, 2026, 12:03 p.m.