Triple

T13887400
Position Surface form Disambiguated ID Type / Status
Subject Forest Survey of India E333881 entity
Predicate shortName P43 FINISHED
Object FSI
FSI is an Indian government agency responsible for conducting nationwide forest resource assessments and providing data for forest management and policy planning.
 E1068687 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: FSI | Statement: [Forest Survey of India, shortName, FSI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FSI
Context triple: [Forest Survey of India, shortName, FSI]
  • A. FSI
    FSI is the FAA airport code for Henry Post Army Airfield, a U.S. Army airfield located at Fort Sill, Oklahoma.
  • B. FSI
    FSI is the common abbreviation for F# Interactive, the interactive REPL environment for the F# programming language.
  • C. FSI
    FSI is the U.S. Department of State’s primary training institution for American diplomats and other foreign affairs professionals.
  • D. FSB
    The FSB (Federal Security Service) is Russia’s principal domestic security and intelligence agency, serving as the main successor to the Soviet-era KGB.
  • E. FSB
    FSB is an international body that monitors and makes recommendations about the global financial system to promote stability and reduce systemic risk.
  • 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: FSI
Triple: [Forest Survey of India, shortName, FSI]
Generated description
FSI is an Indian government agency responsible for conducting nationwide forest resource assessments and providing data for forest management and policy planning.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FSI
Target entity description: FSI is an Indian government agency responsible for conducting nationwide forest resource assessments and providing data for forest management and policy planning.
  • A. FSI
    FSI is the U.S. Department of State’s primary training institution for American diplomats and other foreign affairs professionals.
  • B. FSI
    FSI is the FAA airport code for Henry Post Army Airfield, a U.S. Army airfield located at Fort Sill, Oklahoma.
  • C. FSI
    FSI is the common abbreviation for F# Interactive, the interactive REPL environment for the F# programming language.
  • D. FSB
    The FSB (Federal Security Service) is Russia’s principal domestic security and intelligence agency, serving as the main successor to the Soviet-era KGB.
  • E. FSB
    FSB is an international body that monitors and makes recommendations about the global financial system to promote stability and reduce systemic risk.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de23a281e481908a6184bcd7f59c03 completed April 14, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c718140c8190a625da87231ee814 completed May 3, 2026, 10:07 p.m.
NEDg Description generation batch_69f7c83a3e04819097b6e0b5a3161b9a completed May 3, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69f7c9732d188190a8a7151d21e0a310 completed May 3, 2026, 10:17 p.m.
Created at: April 9, 2026, 10:15 p.m.