Triple

T16985239
Position Surface form Disambiguated ID Type / Status
Subject Nałęczów E412047 entity
Predicate hasCarPlatesCode P26915 FINISHED
Object LPU
LPU is the vehicle registration code assigned to the town of Nałęczów in Poland.
E1244302 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: LPU | Statement: [Nałęczów, hasCarPlatesCode, LPU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LPU
Context triple: [Nałęczów, hasCarPlatesCode, LPU]
  • A. UNILU
    UNILU is the abbreviation for the University of Lucerne, a Swiss higher education institution known for its focus on law, economics, social sciences, theology, and cultural studies.
  • B. LPU Laguna
    LPU Laguna is a satellite campus of Lyceum of the Philippines University located in Laguna, offering higher education programs in various fields.
  • C. LPU Davao
    LPU Davao is a campus of Lyceum of the Philippines University located in Davao City, offering higher education programs under the LPU system.
  • D. UNLU
    UNLU is the acronym for the Unified National Leadership of the Uprising, a coordinating body of Palestinian factions that directed much of the first Intifada against Israeli occupation in the late 1980s.
  • E. IPU
    IPU (Intelligence Processing Unit) is Graphcore's specialized processor architecture designed to accelerate machine learning and artificial intelligence workloads.
  • 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: LPU
Triple: [Nałęczów, hasCarPlatesCode, LPU]
Generated description
LPU is the vehicle registration code assigned to the town of Nałęczów in Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LPU
Target entity description: LPU is the vehicle registration code assigned to the town of Nałęczów in Poland.
  • A. UNILU
    UNILU is the abbreviation for the University of Lucerne, a Swiss higher education institution known for its focus on law, economics, social sciences, theology, and cultural studies.
  • B. LPU Laguna
    LPU Laguna is a satellite campus of Lyceum of the Philippines University located in Laguna, offering higher education programs in various fields.
  • C. LPU Davao
    LPU Davao is a campus of Lyceum of the Philippines University located in Davao City, offering higher education programs under the LPU system.
  • D. UNLU
    UNLU is the acronym for the Unified National Leadership of the Uprising, a coordinating body of Palestinian factions that directed much of the first Intifada against Israeli occupation in the late 1980s.
  • E. IPU
    IPU (Intelligence Processing Unit) is Graphcore's specialized processor architecture designed to accelerate machine learning and artificial intelligence workloads.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18af95c8190a25ef0614e1a17f3 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1109a081908890bbd5958c76c2 completed May 10, 2026, 7:27 p.m.
NEDg Description generation batch_6a0114d5aeb0819086f1a5d279ac0d0f completed May 10, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a0115c583608190bf07ac205399f253 completed May 10, 2026, 11:33 p.m.
Created at: April 10, 2026, 5:32 a.m.