Triple

T3414036
Position Surface form Disambiguated ID Type / Status
Subject PADL E71964 entity
Predicate relatedTo P37 FINISHED
Object LOPSTR
LOPSTR is an international symposium focused on logic-based program development and transformation, bringing together research on program synthesis, analysis, verification, and related areas.
E355617 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: LOPSTR | Statement: [PADL, relatedTo, LOPSTR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LOPSTR
Context triple: [PADL, relatedTo, LOPSTR]
  • A. 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.
  • B. l_P
    l_P is the standard symbol denoting the Planck length, the fundamental quantum scale of length in theoretical physics.
  • C. Lopik
    Lopik is a rural municipality and town in the central Netherlands, known for its agricultural landscape and location along the river Lek.
  • D. Lopatin
    Lopatin is a Russian surname borne by various notable individuals in fields such as the military, arts, and academia.
  • E. Loopt
    Loopt was an early location-based social networking mobile app startup that allowed users to share their real-time location with friends.
  • 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: LOPSTR
Triple: [PADL, relatedTo, LOPSTR]
Generated description
LOPSTR is an international symposium focused on logic-based program development and transformation, bringing together research on program synthesis, analysis, verification, and related areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LOPSTR
Target entity description: LOPSTR is an international symposium focused on logic-based program development and transformation, bringing together research on program synthesis, analysis, verification, and related areas.
  • A. 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.
  • B. l_P
    l_P is the standard symbol denoting the Planck length, the fundamental quantum scale of length in theoretical physics.
  • C. Lopik
    Lopik is a rural municipality and town in the central Netherlands, known for its agricultural landscape and location along the river Lek.
  • D. Lopatin
    Lopatin is a Russian surname borne by various notable individuals in fields such as the military, arts, and academia.
  • E. Loopt
    Loopt was an early location-based social networking mobile app startup that allowed users to share their real-time location with friends.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb927e8d081908a5ab283da93beb2 completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34be16dd48190a51f4e13a6a13a4f completed March 12, 2026, 11:27 p.m.
NEDg Description generation batch_69b34e4972008190af3b84f26b4a3629 completed March 12, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_69b34fc6c3f88190ba1a08243232df05 completed March 12, 2026, 11:44 p.m.
Created at: March 8, 2026, 3:15 p.m.