Triple

T15447432
Position Surface form Disambiguated ID Type / Status
Subject Evrytania regional unit E370060 entity
Predicate administrativeCenter P1474 FINISHED
Object Karpenisi E251604 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: Karpenisi | Statement: [Evrytania regional unit, administrativeCenter, Karpenisi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karpenisi
Context triple: [Evrytania regional unit, administrativeCenter, Karpenisi]
  • A. Karpenisi chosen
    Karpenisi is a small mountainous town in central Greece known for its scenic landscapes, winter sports, and traditional Greek character.
  • B. Kastraki
    Kastraki is a traditional village in central Greece, best known as a gateway to the Meteora rock formations and monasteries.
  • C. Tsigrado
    Tsigrado is a small, secluded cove beach on the Greek island of Milos, known for its dramatic cliffs, turquoise waters, and access via a steep ladder descent.
  • D. Vonitsa
    Vonitsa is a coastal town in western Greece, situated on the Ambracian Gulf and known for its Venetian castle and scenic waterfront.
  • E. Vourgareli
    Vourgareli is a traditional mountain village in the Tzoumerka region of Epirus, Greece, known for its natural beauty and historical 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d42977881909ed07b58c029cbe9 completed May 9, 2026, 1:57 p.m.
Created at: April 10, 2026, 3:21 a.m.