Triple
T17473485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itäkeskus station |
E425476
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object | M1 |
—
|
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: M1 | Statement: [Itäkeskus station, line, M1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M1 Context triple: [Itäkeskus station, line, M1]
-
A.
M1
M1 is a major Hungarian motorway that connects the capital city Budapest with the Austrian border, forming part of a key international transport corridor.
-
B.
M1
M1 is a major north–south urban freeway in Johannesburg, South Africa, connecting the city center with key suburbs and routes.
-
C.
M1
M1 is the main primary mirror of the Extremely Large Telescope, responsible for collecting and focusing incoming light for its observations.
-
D.
M1
M1 is a major Irish motorway that connects Dublin to the border with Northern Ireland, forming part of the primary route between the Republic of Ireland and Belfast.
-
E.
M1
chosen
M1 is one of the main metro lines in the Helsinki public transport system, serving key districts across the Helsinki metropolitan area.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451b990848190b2e8510d67e94b79 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.