Triple

T3044244
Position Surface form Disambiguated ID Type / Status
Subject Karush–Kuhn–Tucker conditions E83405 entity
Predicate alsoKnownAs P39 FINISHED
Object KKT conditions
KKT conditions are a set of necessary (and under certain conditions, sufficient) optimality conditions used in nonlinear programming to characterize solutions of constrained optimization problems.
 E321097 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: KKT conditions | Statement: [Karush–Kuhn–Tucker conditions, alsoKnownAs, KKT conditions]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KKT conditions
Context triple: [Karush–Kuhn–Tucker conditions, alsoKnownAs, KKT conditions]
  • A. Koopmans
    Koopmans is a Dutch surname most notably associated with Nobel Prize–winning economist Tjalling C. Koopmans.
  • B. Kt
    Kt is the post-nominal abbreviation used to denote a Knight Bachelor in the British honours system.
  • C. KCLT
    KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
  • D. NP-KTM
    NP-KTM is the regional code designating the Kathmandu area in Nepal, commonly used in administrative and geographic referencing.
  • E. QKE
    QKE is the IATA airport code for Kleine-Brogel Air Base, a military airfield in Belgium.
  • 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: KKT conditions
Triple: [Karush–Kuhn–Tucker conditions, alsoKnownAs, KKT conditions]
Generated description
KKT conditions are a set of necessary (and under certain conditions, sufficient) optimality conditions used in nonlinear programming to characterize solutions of constrained optimization problems.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KKT conditions
Target entity description: KKT conditions are a set of necessary (and under certain conditions, sufficient) optimality conditions used in nonlinear programming to characterize solutions of constrained optimization problems.
  • A. Koopmans
    Koopmans is a Dutch surname most notably associated with Nobel Prize–winning economist Tjalling C. Koopmans.
  • B. Kt
    Kt is the post-nominal abbreviation used to denote a Knight Bachelor in the British honours system.
  • C. KCLT
    KCLT is the ICAO airport code for Charlotte Douglas International Airport, a major commercial aviation hub serving Charlotte, North Carolina.
  • D. NP-KTM
    NP-KTM is the regional code designating the Kathmandu area in Nepal, commonly used in administrative and geographic referencing.
  • E. QKE
    QKE is the IATA airport code for Kleine-Brogel Air Base, a military airfield in Belgium.
  • 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_69ad8b24924c8190a9bb6f61d519e4ae completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b5ec5988190b8b6c95c743c6d1e completed March 8, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ded35e008190be7dd72aa7537a3b completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1dfa2fb28819089d7d76d9dc72e06 completed March 11, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69b1e0243a848190bce24d035a79fc0a completed March 11, 2026, 9:35 p.m.
Created at: March 8, 2026, 3:01 p.m.