Triple
T7038420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bohuslän |
E163444
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Grebbestad |
E287284
|
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: Grebbestad | Statement: [Bohuslän, containsTown, Grebbestad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grebbestad Context triple: [Bohuslän, containsTown, Grebbestad]
-
A.
Grebbestad
chosen
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
B.
Svarstad
Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
-
C.
Spikkestad
Spikkestad is a village in Asker Municipality, Norway, serving as a terminus on a local commuter rail line and functioning largely as a residential suburb for the Oslo region.
-
D.
Eidskog
Eidskog is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and location along the Swedish border.
-
E.
Kristinestad
Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
- 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_69c6885e7c1c8190be32a8f79ab4e0cf |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e223077c819097992089fa83c563 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9251db3388190b8b0ac7549647887 |
completed | March 29, 2026, 1:11 p.m. |
Created at: March 27, 2026, 2:36 p.m.