Triple
T15293393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Sébastien-sur-Loire |
E365586
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Smiltene |
E1147892
|
NE 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: Smiltene | Statement: [Saint-Sébastien-sur-Loire, hasTwinTown, Smiltene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smiltene Context triple: [Saint-Sébastien-sur-Loire, hasTwinTown, Smiltene]
-
A.
Smiltene
chosen
Smiltene is a small town in northern Latvia known for its scenic surroundings, historical sites, and role as a local administrative and cultural center.
-
B.
Storslett
Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
-
C.
Kaarsild
Kaarsild is a pedestrian arch bridge in Tartu, Estonia, known for spanning the Emajõgi River and offering scenic views of the city.
-
D.
Stöllet
Stöllet is a small locality in central Sweden situated within Torsby Municipality in Värmland County.
-
E.
Hjelset
Hjelset is a village in Møre og Romsdal county, Norway, situated within Molde Municipality along the Romsdalsfjorden.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03682ea488190ac82fdbd0e855d34 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef899e55c8190b1c26491bf37967a |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:15 a.m.