Triple
T29577303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toijala |
E753476
|
entity |
| Predicate | distanceToTampere_km |
P114155
|
FINISHED |
| Object | about 40 |
—
|
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: about 40 | Statement: [Toijala, distanceToTampere_km, about 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTampere_km Context triple: [Toijala, distanceToTampere_km, about 40]
-
A.
distanceToTampere
chosen
Indicates the measured or calculated distance between a given entity’s location and the city of Tampere.
-
B.
distanceToTurku
Indicates the spatial distance between a given entity’s location and the city of Turku.
-
C.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
-
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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a009f53a4948190aef4ede1713e1748 |
completed | May 10, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_6a009edc53d4819080b22c1074a990f3 |
completed | May 10, 2026, 3:06 p.m. |
Created at: April 28, 2026, 6:04 p.m.