Triple

T7275112
Position Surface form Disambiguated ID Type / Status
Subject Battle of Lugos E163006 entity
Predicate location P40 FINISHED
Object Lugos E500225 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: Lugos | Statement: [Battle of Lugos, location, Lugos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lugos
Context triple: [Battle of Lugos, location, Lugos]
  • A. Lugos chosen
    Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
  • B. Luga
    Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
  • C. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • D. Lugo
    Lugo is a historic city in northwestern Spain known for its remarkably well-preserved Roman walls, a UNESCO World Heritage Site.
  • E. Lugo
    Lugo is a historic town and municipality in the Emilia-Romagna region of northern Italy, known for its medieval center and the imposing Rocca Estense fortress.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb0fd8788190aa21d4b2ad773926 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db2c76fc81909632c7ee4e54f81c completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:58 p.m.