Triple

T14887642
Position Surface form Disambiguated ID Type / Status
Subject Abruzzi Apennines E359669 entity
Predicate contains P35 FINISHED
Object Maiella E344593 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: Maiella | Statement: [Abruzzi Apennines, contains, Maiella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maiella
Context triple: [Abruzzi Apennines, contains, Maiella]
  • A. Maiella chosen
    Maiella is a prominent massif in central Italy known for its rugged limestone peaks, deep valleys, and protected landscapes within the Apennine mountain range.
  • B. Monteiasi
    Monteiasi is a small town and comune in the Apulia region of southern Italy, known for its traditional rural character and proximity to the city of Taranto.
  • C. Chiomonte
    Chiomonte is a small Italian mountain town in the Piedmont region, known for its alpine scenery, vineyards, and location in the Susa Valley near the French border.
  • D. Monte Erbas Manna
    Monte Erbas Manna is a mountain peak located within the Gennargentu massif in central Sardinia, Italy.
  • E. Monte Autore
    Monte Autore is a prominent mountain peak in Italy’s central Apennines, known for its scenic views and hiking trails within the Simbruini mountain range.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded5f5b1c88190815f3585770cb135 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe968a17188190bced83ed1006e020 completed May 9, 2026, 2:06 a.m.
Created at: April 10, 2026, 2:08 a.m.