Triple
T5427786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipsi |
E121403
|
entity |
| Predicate | neighboringIsland |
P19482
|
FINISHED |
| Object | Arki |
E121405
|
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: Arki | Statement: [Lipsi, neighboringIsland, Arki]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arki Context triple: [Lipsi, neighboringIsland, Arki]
-
A.
Arki
chosen
Arki is a small, sparsely populated Greek island in the Aegean Sea, known for its quiet beaches and traditional fishing community.
-
B.
Arke
Arke was a Dutch leisure airline and tour operator brand that later became part of TUI and was rebranded as TUI fly Netherlands.
-
C.
Aru
Aru is a town in the northeastern Democratic Republic of the Congo, near the Ugandan border, serving as a local administrative and trading center in Ituri Province.
-
D.
Arkesini
Arkesini is a small traditional village on the Greek island of Amorgos, known for its ancient ruins and scenic Aegean setting.
-
E.
Arka
Arka is a Polish sports club best known for its professional football team based in the port city of Gdynia.
- 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_69bd463c65f0819082ee6483ab4b466a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd881998308190a071af0fe44997bc |
completed | March 20, 2026, 5:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf3ac2e1e88190a624ba277eca3d03 |
completed | March 22, 2026, 12:41 a.m. |
Created at: March 20, 2026, 2:06 p.m.