Triple

T9634393
Position Surface form Disambiguated ID Type / Status
Subject The Definition of Standard ML E232891 entity
Predicate influenced P9 FINISHED
Object MLton E807595 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: MLton | Statement: [The Definition of Standard ML, influenced, MLton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MLton
Context triple: [The Definition of Standard ML, influenced, MLton]
  • A. MLton chosen
    MLton is a whole-program optimizing compiler for the Standard ML programming language, known for its aggressive optimizations and high-performance native code generation.
  • B. MLT
    MLT is the three-letter ISO 3166-1 alpha-3 country code assigned to Malta.
  • C. Tirora
    Tirora is a town in the Gondia district of Maharashtra, India, known for its agricultural surroundings and regional commercial activity.
  • D. Talbo
    Talbo is the surname of Dolly Talbo, a character whose last name identifies her within her fictional or narrative family lineage.
  • E. Merkle
    Merkle is a surname most prominently associated with Ralph Merkle, a pioneering computer scientist and cryptographer known for his foundational work in public-key cryptography and Merkle trees.
  • 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b2a0e2c8190ab5aaa223b1e1cde completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18237e2608190a3e7d45231a35efd completed April 4, 2026, 9:27 p.m.
Created at: March 30, 2026, 8:11 p.m.