Triple

T7918772
Position Surface form Disambiguated ID Type / Status
Subject Zarya E183891 entity
Predicate alsoKnownAs P39 FINISHED
Object FGB
FGB, better known as Zarya, is the first module of the International Space Station, providing initial power and propulsion functions.
 E696970 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: FGB | Statement: [Zarya, alsoKnownAs, FGB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FGB
Context triple: [Zarya, alsoKnownAs, FGB]
  • A. FGN
    FGN is the acronym commonly used to refer to the federal-level governing authority of the Federal Republic of Nigeria.
  • B. FGZ
    FGZ is the FAA location identifier assigned to Sabre Army Heliport, a U.S. Army helicopter facility.
  • C. FGP
    FGP is the stock ticker symbol for FirstGroup, a leading UK-based transport operator running bus and rail services in the United Kingdom and North America.
  • D. FGS
    FGS is a high-precision optical instrument used on space telescopes to maintain accurate pointing and stabilization during observations.
  • E. FBB
    FBB is the operating company responsible for managing Berlin Brandenburg Airport and related airport facilities in the Berlin region.
  • 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: FGB
Triple: [Zarya, alsoKnownAs, FGB]
Generated description
FGB, better known as Zarya, is the first module of the International Space Station, providing initial power and propulsion functions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FGB
Target entity description: FGB, better known as Zarya, is the first module of the International Space Station, providing initial power and propulsion functions.
  • A. FGN
    FGN is the acronym commonly used to refer to the federal-level governing authority of the Federal Republic of Nigeria.
  • B. FGZ
    FGZ is the FAA location identifier assigned to Sabre Army Heliport, a U.S. Army helicopter facility.
  • C. FGP
    FGP is the stock ticker symbol for FirstGroup, a leading UK-based transport operator running bus and rail services in the United Kingdom and North America.
  • D. FGS
    FGS is a high-precision optical instrument used on space telescopes to maintain accurate pointing and stabilization during observations.
  • E. FBB
    FBB is the operating company responsible for managing Berlin Brandenburg Airport and related airport facilities in the Berlin region.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a8fbbb48190b50def4941761a31 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5beea7988190972f7d02881d98f6 completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb5f20eb3c81909e059d5a02263aa2 completed March 31, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cb76bb9a308190a9d7b34838d696db completed March 31, 2026, 7:24 a.m.
Created at: March 30, 2026, 5:05 p.m.