Triple
T6194284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kvarner Gulf |
E138470
|
entity |
| Predicate | hasCoastalTown |
P969
|
FINISHED |
| Object | Bakar |
E313752
|
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: Bakar | Statement: [Kvarner Gulf, hasCoastalTown, Bakar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bakar Context triple: [Kvarner Gulf, hasCoastalTown, Bakar]
-
A.
Bakar
chosen
Bakar is a historic coastal town and port on the Adriatic Sea in western Croatia.
-
B.
Bakish
Bakish is the surname of Bob Bakish, an American media executive best known as the former president and CEO of Paramount Global (formerly ViacomCBS).
-
C.
Bara
Bara is a town in Pakistan’s Khyber District, known as a key settlement in the Khyber Pass region with strategic and commercial significance.
-
D.
Pekat
Pekat is a settlement on the Indonesian island of Sumbawa that was devastated by the catastrophic 1815 eruption of Mount Tambora.
-
E.
Barshaini
Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
- 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_69c008ab9b3081908a11b2c744838435 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062443cec81909dc9bafea2f5e7d4 |
completed | March 22, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f1c162081909cf34e827f1bd7d7 |
completed | March 23, 2026, 4:49 p.m. |
Created at: March 22, 2026, 4:19 p.m.