Triple
T19093187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Märsta Station |
E467339
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object | Mär |
—
|
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: Mär | Statement: [Märsta Station, hasStationCode, Mär]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mär Context triple: [Märsta Station, hasStationCode, Mär]
-
A.
Märsta
chosen
Märsta is a town in Stockholm County, Sweden, known as a residential and transport hub near Stockholm Arlanda Airport.
-
B.
Marrar
Marrar is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural community and country lifestyle.
-
C.
Maretz
Maretz is a small commune in northern France, located in the Nord department within the Hauts-de-France region.
-
D.
Maur
Maur is a municipality in the canton of Zürich in Switzerland, located on the northeastern shore of Lake Greifen and known for its residential character and natural surroundings.
-
E.
Maarn
Maarn is a village in the Dutch province of Utrecht, known for its location on the Utrechtse Heuvelrug ridge and its surrounding natural landscapes.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e34cf5e481908e1f180dacd5602f |
completed | April 20, 2026, 8:26 a.m. |
Created at: April 10, 2026, 12:04 p.m.