Triple
T21123101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kras |
E520481
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Komen |
—
|
NE NERFINISHED |
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: Komen | Statement: [Kras, hasSettlement, Komen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Komen Context triple: [Kras, hasSettlement, Komen]
-
A.
Komen
Komen is the surname associated with Susan G. Komen, whose name is borne by a major U.S. breast cancer advocacy and research organization.
-
B.
Komen
chosen
Komen is a municipality in western Slovenia’s Littoral region, known for its karst landscape and proximity to the Italian border.
-
C.
Corme
Corme is a coastal village in Galicia, northwestern Spain, known for its fishing heritage and dramatic Atlantic scenery along the Costa da Morte.
-
D.
Koules
Koules is a Venetian-era coastal fortress in Heraklion, Crete, that historically protected the city’s harbor and now serves as a prominent cultural and tourist landmark.
-
E.
Komsi
Komsi is a Finnish surname most notably borne by acclaimed coloratura soprano Anu Komsi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50a623881909c0bbaf4f2c055e7 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72236b2d88190bef9f0cd6924ca92 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 2:55 p.m.