Triple
T10428896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flå |
E245856
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Gol |
E440167
|
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: Gol | Statement: [Flå, borders, Gol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gol Context triple: [Flå, borders, Gol]
-
A.
Gol
chosen
Gol is a municipality in Viken county, Norway, known for its mountainous landscapes, outdoor recreation, and the historic Gol Stave Church replica at the Gordarike family park.
-
B.
Gol Sud
Gol Sud is the southern stand of FC Barcelona's Camp Nou stadium, traditionally home to some of the club’s most passionate supporters.
-
C.
Gol Gol
Gol Gol is a small town in southwestern New South Wales, Australia, situated on the Murray River near Mildura in the Sunraysia agricultural region.
-
D.
Golo
Golo is a masculine given name most notably borne by the German historian and essayist Golo Mann.
-
E.
GOLLOG
GOLLOG is the cargo and logistics division of Brazilian airline GOL Linhas Aéreas Inteligentes, providing air and ground freight services.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4b4b5881908ae23f8efeea482b |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ea554888190bf2ef31e33c0ff14 |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:13 p.m.