Triple

T6845350
Position Surface form Disambiguated ID Type / Status
Subject Sabine Mountains E157879 entity
Predicate near P350 FINISHED
Object city of Rieti E344550 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: city of Rieti | Statement: [Sabine Mountains, near, city of Rieti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Rieti
Context triple: [Sabine Mountains, near, city of Rieti]
  • A. city of Rieti chosen
    The city of Rieti is a historic town in the Lazio region of central Italy, often considered the geographical center of the Italian peninsula.
  • B. Montefiascone
    Montefiascone is a historic hilltop town in Italy’s Lazio region, known for its scenic views over Lake Bolsena and its production of the Est! Est!! Est!!! white wine.
  • C. Civitanova Marche
    Civitanova Marche is a coastal town and popular seaside resort on the Adriatic Sea in the Marche region of central Italy.
  • D. Pomezia
    Pomezia is a modern industrial and residential town in the Lazio region of central Italy, situated just south of Rome.
  • E. Viterbo
    Viterbo is a municipality in the Caldas Department of Colombia, known for its coffee production and scenic Andean landscapes.
  • 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_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7ca96008190ba79563c2a9a9b0e completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72fc42e688190baa8413883e5506c completed March 28, 2026, 1:32 a.m.
Created at: March 27, 2026, 2:19 p.m.