Triple

T7033492
Position Surface form Disambiguated ID Type / Status
Subject FreeHand E163323 entity
Predicate fileFormat P130 FINISHED
Object FH9
FH9 is a proprietary vector graphics file format associated with Macromedia FreeHand version 9, used for storing illustrations and design layouts.
 E637127 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: FH9 | Statement: [FreeHand, fileFormat, FH9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FH9
Context triple: [FreeHand, fileFormat, FH9]
  • A. FH
    FH is the vehicle registration code used on license plates for the emirate of Fujairah in the United Arab Emirates.
  • B. FH77A
    FH77A is a Swedish 155 mm towed field howitzer variant known for its relatively advanced loading system and use in modern artillery forces.
  • C. FHU
    FHU is the national governing body responsible for overseeing and developing ice hockey in Ukraine.
  • D. FHU
    FHU is the IATA airport code for Libby Army Airfield, a joint-use military and civilian airport serving the Fort Huachuca area in Arizona, United States.
  • E. HF
    HF is the Faculty of Humanities at the University of Oslo, encompassing disciplines such as languages, history, culture, and philosophy.
  • 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: FH9
Triple: [FreeHand, fileFormat, FH9]
Generated description
FH9 is a proprietary vector graphics file format associated with Macromedia FreeHand version 9, used for storing illustrations and design layouts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FH9
Target entity description: FH9 is a proprietary vector graphics file format associated with Macromedia FreeHand version 9, used for storing illustrations and design layouts.
  • A. FH
    FH is the vehicle registration code used on license plates for the emirate of Fujairah in the United Arab Emirates.
  • B. FH77A
    FH77A is a Swedish 155 mm towed field howitzer variant known for its relatively advanced loading system and use in modern artillery forces.
  • C. FHU
    FHU is the national governing body responsible for overseeing and developing ice hockey in Ukraine.
  • D. FHU
    FHU is the IATA airport code for Libby Army Airfield, a joint-use military and civilian airport serving the Fort Huachuca area in Arizona, United States.
  • E. HF
    HF is the Faculty of Humanities at the University of Oslo, encompassing disciplines such as languages, history, culture, and philosophy.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e2118fc88190a0751ca18eafb4a5 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7759c8e408190a7d457e77a44ee26 completed March 28, 2026, 6:30 a.m.
NEDg Description generation batch_69c779acac2881909917e12072f66637 completed March 28, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_69c77a0390248190ba535e7d931a4682 completed March 28, 2026, 6:49 a.m.
Created at: March 27, 2026, 2:36 p.m.