Triple

T11561830
Position Surface form Disambiguated ID Type / Status
Subject Monte Ferro E274161 entity
Predicate hasName P744 FINISHED
Object Monte Ferro
Monte Ferro is a mountain whose name, meaning “Iron Mountain” in Italian, suggests a rugged, possibly mineral-rich peak often associated with hiking and natural scenery.
 E274161 NE FINISHED

How this triple was built (4 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: Monte Ferro | Statement: [Monte Ferro, hasName, Monte Ferro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monte Ferro
Context triple: [Monte Ferro, hasName, Monte Ferro]
  • A. Monte Ferro
    Monte Ferro is a mountain peak located within the Madonie mountain range in northern Sicily, Italy.
  • B. Monte Granero
    Monte Granero is a prominent mountain peak in the western Italian Alps, known for its rugged terrain and scenic alpine landscapes.
  • C. Monte Penoso
    Monte Penoso is the tallest mountain on the Cape Verdean island of Maio, known as its most prominent natural landmark.
  • D. Cerro Hudson
    Cerro Hudson is a large, glacier-covered stratovolcano in southern Chile known for its highly explosive eruptions and significant impact on regional climate and landscapes.
  • E. Monte Clérigo
    Monte Clérigo is a small coastal village in Portugal’s Algarve region, known for its scenic beach, rugged cliffs, and relaxed seaside atmosphere.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Monte Ferro
Triple: [Monte Ferro, hasName, Monte Ferro]
Generated description
Monte Ferro is a mountain whose name, meaning “Iron Mountain” in Italian, suggests a rugged, possibly mineral-rich peak often associated with hiking and natural scenery.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monte Ferro
Target entity description: Monte Ferro is a mountain whose name, meaning “Iron Mountain” in Italian, suggests a rugged, possibly mineral-rich peak often associated with hiking and natural scenery.
  • A. Monte Ferro chosen
    Monte Ferro is a mountain peak located within the Madonie mountain range in northern Sicily, Italy.
  • B. Monte Granero
    Monte Granero is a prominent mountain peak in the western Italian Alps, known for its rugged terrain and scenic alpine landscapes.
  • C. Monte Penoso
    Monte Penoso is the tallest mountain on the Cape Verdean island of Maio, known as its most prominent natural landmark.
  • D. Cerro Hudson
    Cerro Hudson is a large, glacier-covered stratovolcano in southern Chile known for its highly explosive eruptions and significant impact on regional climate and landscapes.
  • E. Monte Clérigo
    Monte Clérigo is a small coastal village in Portugal’s Algarve region, known for its scenic beach, rugged cliffs, and relaxed seaside atmosphere.
  • F. None of above.

Provenance (5 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_69d6aae4dfa48190a3ab0b19a159a3c5 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd2016481909b33848af3d1d6c1 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e713bcc0048190bec14ac4ab84d51d completed April 21, 2026, 6:05 a.m.
NEDg Description generation batch_69e720f4015c81909ba7973c3e781985 completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e75a7a04c88190bb8f3dd3f3e435ef completed April 21, 2026, 11:07 a.m.
Created at: April 8, 2026, 9:37 p.m.