Triple

T5560013
Position Surface form Disambiguated ID Type / Status
Subject Advanced Passenger Train E145741 entity
Predicate prototypeDesignation P43658 FINISHED
Object APT-E E532313 NE FINISHED

How this triple was built (2 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: APT-E | Statement: [Advanced Passenger Train, prototypeDesignation, APT-E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: APT-E
Context triple: [Advanced Passenger Train, prototypeDesignation, APT-E]
  • A. APT-E chosen
    APT-E was an experimental British tilting high-speed train prototype developed in the 1970s to test advanced technologies for the Advanced Passenger Train program.
  • B. APT
    APT is a widely used command-line package management tool for installing, updating, and removing software on Debian-based Linux systems.
  • C. AET
    AET is the former stock ticker symbol for Aetna Inc., a major U.S. health insurance and managed care company.
  • D. ATE
    ATE is a U.S. National Science Foundation program that supports the education and training of technicians for advanced technology fields through partnerships between two-year colleges, industry, and other educational institutions.
  • E. Ettercap
    Ettercap is a network security tool used for sniffing, intercepting, and manipulating traffic on local area networks, commonly employed for man-in-the-middle attacks and protocol analysis.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c008fcaf788190bafa02a1917ee73b completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020167afc8190b0c518907cd0d99b completed March 22, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07d7658a481909e9e9b29df2b148e completed March 22, 2026, 11:38 p.m.
Created at: March 22, 2026, 3:36 p.m.