Triple
T36873252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parola railway station |
E911276
|
entity |
| Predicate | distanceFromTampereByRail |
P114155
|
FINISHED |
| Object | approximately 80 km |
—
|
LITERAL 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: approximately 80 km | Statement: [Parola railway station, distanceFromTampereByRail, approximately 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTampereByRail Context triple: [Parola railway station, distanceFromTampereByRail, approximately 80 km]
-
A.
distanceToTampere
chosen
Indicates the measured or calculated distance between a given entity’s location and the city of Tampere.
-
B.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
-
C.
distanceToTurku
Indicates the spatial distance between a given entity’s location and the city of Turku.
-
D.
distanceToTurkuApproxKm
Indicates an approximate physical distance, measured in kilometers, between a given entity and the city of Turku.
-
E.
distanceToHelsinki_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Helsinki.
- F. None of above.
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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.