Triple

T12494731
Position Surface form Disambiguated ID Type / Status
Subject The Coroner’s Toolkit E298653 entity
Predicate influenced P9 FINISHED
Object The Sleuth Kit E192917 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: The Sleuth Kit | Statement: [The Coroner’s Toolkit, influenced, The Sleuth Kit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Sleuth Kit
Context triple: [The Coroner’s Toolkit, influenced, The Sleuth Kit]
  • A. sleuthkit chosen
    Sleuth Kit is an open-source digital forensics toolkit used to analyze disk images and recover evidence from file systems.
  • B. OpenText EnCase
    OpenText EnCase is a widely used digital forensics and incident response software suite for acquiring, analyzing, and preserving electronic evidence in legal and cybersecurity investigations.
  • C. Maltego
    Maltego is a graphical link analysis and data mining tool widely used in digital forensics and open-source intelligence (OSINT) investigations.
  • D. Wireshark
    Wireshark is a widely used open-source network protocol analyzer that captures and interactively inspects traffic on computer networks for troubleshooting, analysis, and security auditing.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de4089c8190917a45365e641437 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64badad488190ae1c6c2883a88a4b completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:56 p.m.