Triple

T11650806
Position Surface form Disambiguated ID Type / Status
Subject Reckitt Benckiser E276898 entity
Predicate tickerSymbol P1447 FINISHED
Object RKT
RKT is the stock ticker symbol for Reckitt Benckiser, a multinational consumer goods company known for health, hygiene, and home products.
 E938965 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: RKT | Statement: [Reckitt Benckiser, tickerSymbol, RKT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RKT
Context triple: [Reckitt Benckiser, tickerSymbol, RKT]
  • A. RKA
    RKA is the Russian Space Agency that managed Russia’s human spaceflight activities, including operations of the Mir space station.
  • B. RKP
    RKP is the Swedish abbreviation for the Swedish People’s Party of Finland, a liberal-centrist political party representing the Swedish-speaking minority in Finland.
  • C. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. RKTN
    RKTN is the ICAO airport code for Daegu International Airport, a major civilian and military airfield serving the city of Daegu in South Korea.
  • 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: RKT
Triple: [Reckitt Benckiser, tickerSymbol, RKT]
Generated description
RKT is the stock ticker symbol for Reckitt Benckiser, a multinational consumer goods company known for health, hygiene, and home products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RKT
Target entity description: RKT is the stock ticker symbol for Reckitt Benckiser, a multinational consumer goods company known for health, hygiene, and home products.
  • A. RKA
    RKA is the Russian Space Agency that managed Russia’s human spaceflight activities, including operations of the Mir space station.
  • B. RKP
    RKP is the Swedish abbreviation for the Swedish People’s Party of Finland, a liberal-centrist political party representing the Swedish-speaking minority in Finland.
  • C. RKR
    RKR is the vehicle registration code assigned to vehicles registered in the Rymanów area of Poland.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. RKTN
    RKTN is the ICAO airport code for Daegu International Airport, a major civilian and military airfield serving the city of Daegu in South Korea.
  • 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_69d6aafbb3c081908a9cdb4ecb8d981d completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a2cea9308190a13f7dd995ea07a4 completed April 10, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee8805a91081909ff29b3357e351ee completed April 26, 2026, 9:47 p.m.
NEDg Description generation batch_69eeb314eef0819091a949bbfc820ee9 completed April 27, 2026, 12:51 a.m.
NED2 Entity disambiguation (via description) batch_69eee9a79d348190bb3e15f0d37b9d57 completed April 27, 2026, 4:44 a.m.
Created at: April 8, 2026, 9:39 p.m.