Triple

T13232368
Position Surface form Disambiguated ID Type / Status
Subject Mount Sannine E315052 entity
Predicate hasVillageOnSlopes P39554 FINISHED
Object Faraya
Faraya is a popular Lebanese mountain village and ski resort town known for its scenic landscapes and winter sports.
E1029591 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: Faraya | Statement: [Mount Sannine, hasVillageOnSlopes, Faraya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faraya
Context triple: [Mount Sannine, hasVillageOnSlopes, Faraya]
  • A. Khidrana
    Khidrana is the former name of Muktsar, a historically significant town in Punjab, India, known for its association with Sikh history and the Battle of Muktsar.
  • B. Yaviza
    Yaviza is a small town in Panama’s Darién Province known as the southern terminus of the Pan-American Highway and a gateway to the remote Darién region.
  • C. Marulan
    Marulan is a small town in New South Wales, Australia, known as a rural service centre located near the geographic midpoint between Sydney and Canberra.
  • D. Mi'ilya
    Mi'ilya is a village in northern Israel, notable for its predominantly Christian Arab population and its location near the city of Ma'alot-Tarshiha.
  • E. Derisha
    Derisha is a lexical form or word used in a linguistic context, likely representing one member of a pair of related terms alongside Perisha.
  • 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: Faraya
Triple: [Mount Sannine, hasVillageOnSlopes, Faraya]
Generated description
Faraya is a popular Lebanese mountain village and ski resort town known for its scenic landscapes and winter sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Faraya
Target entity description: Faraya is a popular Lebanese mountain village and ski resort town known for its scenic landscapes and winter sports.
  • A. Khidrana
    Khidrana is the former name of Muktsar, a historically significant town in Punjab, India, known for its association with Sikh history and the Battle of Muktsar.
  • B. Yaviza
    Yaviza is a small town in Panama’s Darién Province known as the southern terminus of the Pan-American Highway and a gateway to the remote Darién region.
  • C. Marulan
    Marulan is a small town in New South Wales, Australia, known as a rural service centre located near the geographic midpoint between Sydney and Canberra.
  • D. Mi'ilya
    Mi'ilya is a village in northern Israel, notable for its predominantly Christian Arab population and its location near the city of Ma'alot-Tarshiha.
  • E. Derisha
    Derisha is a lexical form or word used in a linguistic context, likely representing one member of a pair of related terms alongside Perisha.
  • F. None of above. chosen

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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d34ff288190bdb550a019b7a470 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff2dca2c81909cab1aa868ad575d completed May 3, 2026, 7:54 a.m.
NEDg Description generation batch_69f70476310c8190b13dc948c1f1ce95 completed May 3, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_69f70578047c819089fc3044eceb4eac completed May 3, 2026, 8:21 a.m.
Created at: April 9, 2026, 9:22 p.m.