Triple

T5307267
Position Surface form Disambiguated ID Type / Status
Subject Hasbro E120132 entity
Predicate tickerSymbol P1447 FINISHED
Object HAS
HAS is the stock ticker symbol for Hasbro, Inc., a major American toy and entertainment company traded on the NASDAQ.
 E510994 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: HAS | Statement: [Hasbro, tickerSymbol, HAS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HAS
Context triple: [Hasbro, tickerSymbol, HAS]
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HAD
    HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
  • C. HA
    HA is the IATA airline designator for Hawaiian Airlines, the largest and longest-serving commercial airline based in Hawaii.
  • D. HAM
    HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
  • E. HAM
    HAM is the standard abbreviation used for the Canadian Football League team, the Hamilton Tiger-Cats.
  • 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: HAS
Triple: [Hasbro, tickerSymbol, HAS]
Generated description
HAS is the stock ticker symbol for Hasbro, Inc., a major American toy and entertainment company traded on the NASDAQ.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HAS
Target entity description: HAS is the stock ticker symbol for Hasbro, Inc., a major American toy and entertainment company traded on the NASDAQ.
  • A. HAV
    HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • B. HAD
    HAD is the commonly used abbreviation for the Historical Astronomy Division, a group focused on the study and promotion of the history of astronomy.
  • C. HA
    HA is the IATA airline designator for Hawaiian Airlines, the largest and longest-serving commercial airline based in Hawaii.
  • D. HAM
    HAM is the IATA airport code for Hamburg Airport, the international airport serving the city of Hamburg, Germany.
  • E. HAM
    HAM is the standard abbreviation used for the Canadian Football League team, the Hamilton Tiger-Cats.
  • 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_69bd44704be88190acdb2ac481b0ff55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd851ee8908190814b695723247016 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10fb59ac8190ad23ea4f77a8c0e7 completed March 21, 2026, 9:43 p.m.
NEDg Description generation batch_69bf11cbcf4c819089369d00c2237f9c completed March 21, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_69bf1226ddd08190a39799fd0db58694 completed March 21, 2026, 9:48 p.m.
Created at: March 20, 2026, 1:53 p.m.