Triple

T12994991
Position Surface form Disambiguated ID Type / Status
Subject Landelijke Knokploegen E322009 entity
Predicate cooperatedWith P435 FINISHED
Object LO-LKP
LO-LKP was a Dutch World War II resistance organization that coordinated underground activities such as hiding people and conducting sabotage against the German occupation.
 E1015822 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: LO-LKP | Statement: [Landelijke Knokploegen, cooperatedWith, LO-LKP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LO-LKP
Context triple: [Landelijke Knokploegen, cooperatedWith, LO-LKP]
  • A. LKO
    LKO is the IATA airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
  • B. LOP
    LOP is the IATA airport code for Lombok International Airport, the main air gateway to the Indonesian island of Lombok.
  • C. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • D. LOP-G
    LOP-G is the Lunar Orbital Platform-Gateway, a planned crew-tended space station in lunar orbit that will serve as a staging point for deep space exploration missions.
  • E. Looj
    Looj is a gutter-cleaning robot developed by iRobot to automate the removal of debris from residential gutters.
  • 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: LO-LKP
Triple: [Landelijke Knokploegen, cooperatedWith, LO-LKP]
Generated description
LO-LKP was a Dutch World War II resistance organization that coordinated underground activities such as hiding people and conducting sabotage against the German occupation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LO-LKP
Target entity description: LO-LKP was a Dutch World War II resistance organization that coordinated underground activities such as hiding people and conducting sabotage against the German occupation.
  • A. LKO
    LKO is the IATA airport code for Chaudhary Charan Singh International Airport serving Lucknow, India.
  • B. LOP
    LOP is the IATA airport code for Lombok International Airport, the main air gateway to the Indonesian island of Lombok.
  • C. LÖ
    LÖ is the vehicle registration code for the district of Lörrach in the German state of Baden-Württemberg.
  • D. LOP-G
    LOP-G is the Lunar Orbital Platform-Gateway, a planned crew-tended space station in lunar orbit that will serve as a staging point for deep space exploration missions.
  • E. Looj
    Looj is a gutter-cleaning robot developed by iRobot to automate the removal of debris from residential gutters.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e7877f481908a03f1077600e58a completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0fca5e4819086b010fdd1813419 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c20a1eb881908a28dc884c2005ef completed May 3, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f6c34b9ec08190bb29458b6f43c388 completed May 3, 2026, 3:38 a.m.
Created at: April 9, 2026, 8:44 p.m.