Triple

T10807452
Position Surface form Disambiguated ID Type / Status
Subject Fellow of the Indian National Science Academy E255004 entity
Predicate abbreviation P43 FINISHED
Object FNA
FNA is a prestigious scientific honorific title awarded to elected Fellows of the Indian National Science Academy.
 E888028 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: FNA | Statement: [Fellow of the Indian National Science Academy, abbreviation, FNA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FNA
Context triple: [Fellow of the Indian National Science Academy, abbreviation, FNA]
  • A. FNI
    FNI is the IATA airport code for Nîmes-Alès-Camargue-Cévennes Airport in southern France.
  • B. FNH
    FNH is the National Rail station code for Farnham railway station in Surrey, England.
  • C. NFNA
    NFNA is the ICAO airport code assigned to Nausori International Airport in Fiji.
  • D. FNC
    FNC is the IATA airport code for Cristiano Ronaldo Madeira International Airport, the main air gateway to Portugal’s Madeira Island.
  • E. FNS
    FNS is the U.S. Department of Agriculture agency that administers federal food assistance and nutrition programs such as SNAP and school meals.
  • 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: FNA
Triple: [Fellow of the Indian National Science Academy, abbreviation, FNA]
Generated description
FNA is a prestigious scientific honorific title awarded to elected Fellows of the Indian National Science Academy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FNA
Target entity description: FNA is a prestigious scientific honorific title awarded to elected Fellows of the Indian National Science Academy.
  • A. FNI
    FNI is the IATA airport code for Nîmes-Alès-Camargue-Cévennes Airport in southern France.
  • B. FNH
    FNH is the National Rail station code for Farnham railway station in Surrey, England.
  • C. NFNA
    NFNA is the ICAO airport code assigned to Nausori International Airport in Fiji.
  • D. FNC
    FNC is the IATA airport code for Cristiano Ronaldo Madeira International Airport, the main air gateway to Portugal’s Madeira Island.
  • E. FNS
    FNS is the U.S. Department of Agriculture agency that administers federal food assistance and nutrition programs such as SNAP and school meals.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b506488190921e6a1f4168dd9e completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69de8513fe0881909d6833c85aac03a8 completed April 14, 2026, 6:19 p.m.
NEDg Description generation batch_69de8e6f3fac8190bcd1675978d6d6d7 completed April 14, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69de8fa679cc81909cb51035e5403ce9 completed April 14, 2026, 7:04 p.m.
Created at: April 8, 2026, 9:18 p.m.