Triple
T16973433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsambika Beach |
E411745
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Archangelos |
E1210744
|
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: Archangelos | Statement: [Tsambika Beach, hasNearbySettlement, Archangelos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Archangelos Context triple: [Tsambika Beach, hasNearbySettlement, Archangelos]
-
A.
Archangelos
chosen
Archangelos is a town on the island of Rhodes in Greece, known for its traditional character and proximity to popular beaches and historical sites.
-
B.
Vissarion
Vissarion is a masculine given name most notably borne by the influential Russian literary critic Vissarion Belinsky.
-
C.
Saint Gorgonius
Saint Gorgonius is a Christian martyr venerated as a patron saint, particularly honored in regions such as the Diocese of Minden.
-
D.
Varlaam
Varlaam is a boisterous, drunken monk who provides comic relief and political commentary in Modest Mussorgsky’s opera "Boris Godunov."
-
E.
Kosmas
Kosmas is a traditional mountain village in the Parnon range of the southeastern Peloponnese in Greece, known for its scenic setting and historic stone architecture.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0af06688190a77682aa297cd27e |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d4738fbc819099e8281ebc777091 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.