Triple

T12552206
Position Surface form Disambiguated ID Type / Status
Subject Monastir Vilayet E300123 entity
Predicate nowIncludesCity P41762 FINISHED
Object Resen E417355 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: Resen | Statement: [Monastir Vilayet, nowIncludesCity, Resen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Resen
Context triple: [Monastir Vilayet, nowIncludesCity, Resen]
  • A. Resen chosen
    Resen is a small town in southwestern North Macedonia that serves as the administrative and cultural center of the Prespa region near Lake Prespa.
  • B. Romsa
    Romsa is the Northern Sami name for Tromsø, a major city in northern Norway known as a cultural and economic hub above the Arctic Circle.
  • C. Resia
    Resia is a small village in South Tyrol, northern Italy, known for its proximity to the submerged bell tower of Lake Resia in the Reschen Pass.
  • D. Arrifes
    Arrifes is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
  • E. Šolta
    Šolta is a small Croatian island in the Adriatic Sea, known for its tranquil villages, olive groves, and clear bays, located just off the coast from the city of Split.
  • 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_69d6ada707008190aaec1238117c9379 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d960c2e5b88190a7cc16002b218d8a completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f655853ecc8190b178a489d806a0c4 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 9:58 p.m.