Triple

T8588274
Position Surface form Disambiguated ID Type / Status
Subject KNDS E203361 entity
Predicate ownsBrand P1500 FINISHED
Object KMW
KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
 E746200 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: KMW | Statement: [KNDS, ownsBrand, KMW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KMW
Context triple: [KNDS, ownsBrand, KMW]
  • A. KMG
    KMG is the IATA airport code for Kunming Changshui International Airport, a major air transport hub serving Kunming in Yunnan Province, China.
  • B. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • C. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • D. GKW
    GKW is the National Rail station code for Greenock West railway station in Inverclyde, Scotland.
  • E. KMEV
    KMEV is the ICAO airport code for Minden–Tahoe Airport, a public general aviation airport serving the Minden and Lake Tahoe region in Nevada, United States.
  • 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: KMW
Triple: [KNDS, ownsBrand, KMW]
Generated description
KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KMW
Target entity description: KMW is a German defense manufacturer best known for producing armored vehicles such as the Leopard 2 main battle tank.
  • A. KMG
    KMG is the IATA airport code for Kunming Changshui International Airport, a major air transport hub serving Kunming in Yunnan Province, China.
  • B. KMF
    KMF is the ISO 4217 currency code for the Comorian franc, the official monetary unit of the Comoros.
  • C. KMK
    KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
  • D. GKW
    GKW is the National Rail station code for Greenock West railway station in Inverclyde, Scotland.
  • E. KMEV
    KMEV is the ICAO airport code for Minden–Tahoe Airport, a public general aviation airport serving the Minden and Lake Tahoe region in Nevada, United States.
  • 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_69ca8329bb7c8190a63c643730839103 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc466300bc8190aa5659a4e6a9694a completed March 31, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8a51db0819097ec0f70bee31539 completed April 2, 2026, 5:34 p.m.
NEDg Description generation batch_69cea996a5c48190a12ffe8e282d2d9c completed April 2, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69ceadb2d52c8190aada1d797753663e completed April 2, 2026, 5:56 p.m.
Created at: March 30, 2026, 6:23 p.m.