Triple
T5988077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eivissa |
E133277
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object | Eivissa |
E133277
|
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: Eivissa | Statement: [Eivissa, officialName, Eivissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eivissa Context triple: [Eivissa, officialName, Eivissa]
-
A.
Eivissa
chosen
Eivissa is the Catalan name for Ibiza, a popular Mediterranean island in Spain’s Balearic archipelago known for its beaches and nightlife.
-
B.
Borðoy
Borðoy is one of the main islands of the Faroe Islands, known for its rugged landscapes and the town of Klaksvík, the country’s second-largest settlement.
-
C.
Heltermaa
Heltermaa is a small port village on the eastern coast of Hiiumaa Island in Estonia, serving as a key ferry connection to the mainland.
-
D.
Barentu
Barentu is a town in western Eritrea that serves as an important regional center in the Gash-Barka administrative region.
-
E.
Laevsky
Laevsky is the flawed, indecisive antihero of Anton Chekhov’s novella "The Duel," whose moral weakness and personal crisis drive the story’s central conflict.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc51d948190bacf4c40a73e91b2 |
completed | March 22, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c10854969c8190b9be249f26ad2f47 |
completed | March 23, 2026, 9:31 a.m. |
Created at: March 22, 2026, 4:04 p.m.