Triple

T5978942
Position Surface form Disambiguated ID Type / Status
Subject AK-47 E133070 entity
Predicate successor P78 FINISHED
Object AKM E281858 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: AKM | Statement: [AK-47, successor, AKM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AKM
Context triple: [AK-47, successor, AKM]
  • A. AKM chosen
    The AKM is a modernized, widely produced variant of the AK-47 assault rifle, known for its reliability, simplicity, and extensive use in militaries and conflicts around the world.
  • B. AMKC
    AMKC is a large jail facility on Rikers Island in New York City, named after former Correction Commissioner Anna M. Kross.
  • C. KMA
    KMA is the commonly used abbreviation for the Royal Swedish Academy of Music, Sweden’s national institution dedicated to the advancement of musical art and scholarship.
  • D. AMTK
    AMTK is the reporting mark used by Amtrak, the United States’ national passenger railroad service, to identify its locomotives and rolling stock.
  • E. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a3e686c81908910c0881ac1624d completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e41d23848190bc7835eb6313b6a5 completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:04 p.m.