Triple

T6006284
Position Surface form Disambiguated ID Type / Status
Subject Legrand E133717 entity
Predicate tickerSymbol P1447 FINISHED
Object LR
LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
 E561782 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: LR | Statement: [Legrand, tickerSymbol, LR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LR
Context triple: [Legrand, tickerSymbol, LR]
  • A. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • B. RL
    RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
  • C. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • D. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • E. LM
    LM is the Apollo Lunar Module, the spacecraft used by NASA during the Apollo program to land astronauts on the Moon and return them to lunar orbit.
  • 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: LR
Triple: [Legrand, tickerSymbol, LR]
Generated description
LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LR
Target entity description: LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • A. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • B. RL
    RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
  • C. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • D. LM
    LM is the IATA airline designator assigned to Loganair, a regional airline based in Scotland.
  • E. LM
    LM is the Apollo Lunar Module, the spacecraft used by NASA during the Apollo program to land astronauts on the Moon and return them to lunar orbit.
  • 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f128354819088971ee398cbda77 completed March 22, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10895559081908b9efdd32ecef37f completed March 23, 2026, 9:32 a.m.
NEDg Description generation batch_69c10b7467e88190955014bc060b20e4 completed March 23, 2026, 9:44 a.m.
NED2 Entity disambiguation (via description) batch_69c10c0a001c81908e3ca53e9491ff9a completed March 23, 2026, 9:46 a.m.
Created at: March 22, 2026, 4:06 p.m.