Triple

T12645626
Position Surface form Disambiguated ID Type / Status
Subject Nokia E52 E302015 entity
Predicate modelNumber P8607 FINISHED
Object E52
E52 is a Nokia Eseries mobile phone model known for its slim design, long battery life, and business-oriented features.
 E995129 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: E52 | Statement: [Nokia E52, modelNumber, E52]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: E52
Context triple: [Nokia E52, modelNumber, E52]
  • A. E50
    E50 is a major trans-European road corridor that spans multiple countries, facilitating long-distance east–west travel and trade across the continent.
  • B. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • C. E53
    E53 is the internal BMW designation for the first-generation BMW X5 mid-size luxury SUV produced from 1999 to 2006.
  • D. E22
    E22 is a major European route that forms part of the international E-road network, linking multiple countries across Europe.
  • E. S52
    S52 is a bus service route that provides public transportation access to the village of Grasmere.
  • 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: E52
Triple: [Nokia E52, modelNumber, E52]
Generated description
E52 is a Nokia Eseries mobile phone model known for its slim design, long battery life, and business-oriented features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: E52
Target entity description: E52 is a Nokia Eseries mobile phone model known for its slim design, long battery life, and business-oriented features.
  • A. E50
    E50 is a major trans-European road corridor that spans multiple countries, facilitating long-distance east–west travel and trade across the continent.
  • B. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • C. E53
    E53 is the internal BMW designation for the first-generation BMW X5 mid-size luxury SUV produced from 1999 to 2006.
  • D. E22
    E22 is a major European route that forms part of the international E-road network, linking multiple countries across Europe.
  • E. S52
    S52 is a bus service route that provides public transportation access to the village of Grasmere.
  • 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_69d7bdec9f9c8190b4bac675b7588211 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9614cefdc81908cfc4a4d04aa6eda completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6687961d88190a605f17425ad7547 completed May 2, 2026, 9:11 p.m.
NEDg Description generation batch_69f6695372688190b09a2bb2e58cb546 completed May 2, 2026, 9:14 p.m.
NED2 Entity disambiguation (via description) batch_69f669fbb9f88190b0f5cc5bb758d132 completed May 2, 2026, 9:17 p.m.
Created at: April 9, 2026, 5:17 p.m.