Triple

T14420835
Position Surface form Disambiguated ID Type / Status
Subject Logitech E357578 entity
Predicate tickerSymbol P1447 FINISHED
Object LOGI
LOGI is the stock ticker symbol for Logitech International S.A., a global manufacturer of computer peripherals and consumer electronics.
 E1099392 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: LOGI | Statement: [Logitech, tickerSymbol, LOGI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LOGI
Context triple: [Logitech, tickerSymbol, LOGI]
  • A. Loggos
    Loggos is a small, picturesque coastal village on the Greek island of Paxos, known for its harbor, traditional tavernas, and relaxed atmosphere.
  • B. Logatec
    Logatec is a town and municipality in western Slovenia known for its forests, karst landscape, and position as a transport hub between Ljubljana and the Slovenian coast.
  • C. product logarithm
    The product logarithm is a special function, commonly denoted as the Lambert W function, that serves as the inverse of f(w) = w e^w and is widely used in solving equations involving exponentials and products.
  • D. LG 1
    LG 1 is the abbreviated designation for Training Wing 1, a military aviation training formation.
  • E. BLU
    BLU is the vehicle registration code used on license plates for the city of Blumenau in the state of Santa Catarina, Brazil.
  • 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: LOGI
Triple: [Logitech, tickerSymbol, LOGI]
Generated description
LOGI is the stock ticker symbol for Logitech International S.A., a global manufacturer of computer peripherals and consumer electronics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LOGI
Target entity description: LOGI is the stock ticker symbol for Logitech International S.A., a global manufacturer of computer peripherals and consumer electronics.
  • A. Loggos
    Loggos is a small, picturesque coastal village on the Greek island of Paxos, known for its harbor, traditional tavernas, and relaxed atmosphere.
  • B. Logatec
    Logatec is a town and municipality in western Slovenia known for its forests, karst landscape, and position as a transport hub between Ljubljana and the Slovenian coast.
  • C. product logarithm
    The product logarithm is a special function, commonly denoted as the Lambert W function, that serves as the inverse of f(w) = w e^w and is widely used in solving equations involving exponentials and products.
  • D. LG 1
    LG 1 is the abbreviated designation for Training Wing 1, a military aviation training formation.
  • E. BLU
    BLU is the vehicle registration code used on license plates for the city of Blumenau in the state of Santa Catarina, Brazil.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de910eb354819089d5d5a46919eb49 completed April 14, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bcb131c8190935d9bacb1afc995 completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5e188a148190bb166b7d50ad3b46 completed May 8, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_69fd5ea592cc8190a47a2f6a511c0549 completed May 8, 2026, 3:55 a.m.
Created at: April 10, 2026, 1:18 a.m.