Triple

T16318395
Position Surface form Disambiguated ID Type / Status
Subject Lindt & Sprüngli E396229 entity
Predicate tickerSymbol P1447 FINISHED
Object LISN
LISN is the stock ticker symbol for Chocoladefabriken Lindt & Sprüngli AG, the Swiss premium chocolate manufacturer.
E1207023 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: LISN | Statement: [Lindt & Sprüngli, tickerSymbol, LISN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LISN
Context triple: [Lindt & Sprüngli, tickerSymbol, LISN]
  • A. LIS
    LIS is the three-letter IATA airport code for Humberto Delgado Airport, the main international airport serving Lisbon, Portugal.
  • B. Lis
    Lis is a diminutive form of the given name Lisa, commonly used as a short or affectionate variant.
  • C. LISA line
    The LISA line is a route of the CDGVAL automated people mover system serving Paris Charles de Gaulle Airport.
  • D. LNS
    LNS is the commonly used abbreviation for the Laboratory for Nuclear Science, a research institution focused on advancing the understanding of nuclear and particle physics.
  • E. LNS
    LNS is the commonly used abbreviation for Lindsey Nelson Stadium, the University of Tennessee’s baseball venue in Knoxville.
  • 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: LISN
Triple: [Lindt & Sprüngli, tickerSymbol, LISN]
Generated description
LISN is the stock ticker symbol for Chocoladefabriken Lindt & Sprüngli AG, the Swiss premium chocolate manufacturer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LISN
Target entity description: LISN is the stock ticker symbol for Chocoladefabriken Lindt & Sprüngli AG, the Swiss premium chocolate manufacturer.
  • A. LIS
    LIS is the three-letter IATA airport code for Humberto Delgado Airport, the main international airport serving Lisbon, Portugal.
  • B. Lis
    Lis is a diminutive form of the given name Lisa, commonly used as a short or affectionate variant.
  • C. LISA line
    The LISA line is a route of the CDGVAL automated people mover system serving Paris Charles de Gaulle Airport.
  • D. LNS
    LNS is the commonly used abbreviation for the Laboratory for Nuclear Science, a research institution focused on advancing the understanding of nuclear and particle physics.
  • E. LNS
    LNS is the commonly used abbreviation for Lindsey Nelson Stadium, the University of Tennessee’s baseball venue in Knoxville.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e296b3e3e081908a996b3e57ca4e32 completed April 17, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002606f0e0819081f50dae9e6b7a0d completed May 10, 2026, 6:30 a.m.
NEDg Description generation batch_6a00275e44d481909bed62779ea9a0d7 completed May 10, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a0027f99d948190b22812f0c9a2c0ff completed May 10, 2026, 6:38 a.m.
Created at: April 10, 2026, 5:06 a.m.