Triple

T21591403
Position Surface form Disambiguated ID Type / Status
Subject tar (Persian lute) E532786 entity
Predicate relatedInstrument P7726 FINISHED
Object saz (bağlama)
The saz (bağlama) is a long-necked fretted lute widely used in Turkish and other Anatolian folk music traditions as a primary melodic and accompaniment instrument.
 E1492084 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: saz (bağlama) | Statement: [tar (Persian lute), relatedInstrument, saz (bağlama)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: saz (bağlama)
Context triple: [tar (Persian lute), relatedInstrument, saz (bağlama)]
  • A. SAZU
    SAZU is the national academy of sciences and arts of Slovenia, serving as the country’s leading scholarly and artistic institution.
  • B. SAZS
    SAZS is the ICAO airport code for San Carlos de Bariloche Airport, a major gateway to the Patagonia region of Argentina.
  • C. BAZG
    BAZG is the Swiss Federal Office responsible for customs, border security, and related enforcement tasks.
  • D. BAKIZA
    BAKIZA is the official Swahili language council of Zanzibar responsible for promoting, standardizing, and developing Kiswahili in the region.
  • E. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • 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: saz (bağlama)
Triple: [tar (Persian lute), relatedInstrument, saz (bağlama)]
Generated description
The saz (bağlama) is a long-necked fretted lute widely used in Turkish and other Anatolian folk music traditions as a primary melodic and accompaniment instrument.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: saz (bağlama)
Target entity description: The saz (bağlama) is a long-necked fretted lute widely used in Turkish and other Anatolian folk music traditions as a primary melodic and accompaniment instrument.
  • A. SAZU
    SAZU is the national academy of sciences and arts of Slovenia, serving as the country’s leading scholarly and artistic institution.
  • B. SAZS
    SAZS is the ICAO airport code for San Carlos de Bariloche Airport, a major gateway to the Patagonia region of Argentina.
  • C. BAZG
    BAZG is the Swiss Federal Office responsible for customs, border security, and related enforcement tasks.
  • D. BAKIZA
    BAKIZA is the official Swahili language council of Zanzibar responsible for promoting, standardizing, and developing Kiswahili in the region.
  • E. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eefaddc8508190950b31e2df865ad1 completed April 27, 2026, 5:57 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09f681f8a08190965cf2c3b12eb134 completed May 17, 2026, 5:10 p.m.
NEDg Description generation batch_6a09f85e21948190a6563d309c349f78 completed May 17, 2026, 5:18 p.m.
NED2 Entity disambiguation (via description) batch_6a09f8d30ff08190b3bc6c45f7b5257b completed May 17, 2026, 5:20 p.m.
Created at: April 16, 2026, 6:32 p.m.