Triple

T5290665
Position Surface form Disambiguated ID Type / Status
Subject Vy regional trains E119732 entity
Predicate serves P98 FINISHED
Object Hamar E68670 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: Hamar | Statement: [Vy regional trains, serves, Hamar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamar
Context triple: [Vy regional trains, serves, Hamar]
  • A. Hamar chosen
    Hamar is a town and municipality in Innlandet county, Norway, known for its rich Viking history and as a regional cultural and administrative center.
  • B. Garmsar
    Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
  • C. Sassoun
    Sassoun is a mountainous region in historic Western Armenia, famed in Armenian folklore as the homeland of the legendary heroes of the national epic.
  • D. Hadrut
    Hadrut is a town in the Nagorno-Karabakh region, historically part of the Shusha uezd, known for its strategic location and role in regional conflicts between Armenia and Azerbaijan.
  • E. Hatti
    Hatti was an ancient Anatolian kingdom and cultural region centered in central Turkey, later absorbed into the Hittite Empire.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06f066988190a3df7e270df84fdd completed March 21, 2026, 9 p.m.
Created at: March 20, 2026, 1:52 p.m.