Triple

T7600757
Position Surface form Disambiguated ID Type / Status
Subject Kenneth Arrow E179975 entity
Predicate familyName P18 FINISHED
Object Arrow
Arrow is a common English surname borne by various individuals, including the influential economist Kenneth Arrow.
E674931 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: Arrow | Statement: [Kenneth Arrow, familyName, Arrow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arrow
Context triple: [Kenneth Arrow, familyName, Arrow]
  • A. Arrow
    Arrow is a popular American superhero television series based on the DC Comics character Green Arrow, known for launching the interconnected "Arrowverse" franchise.
  • B. Arrow
    Arrow is the English translation of "Freccia," the nickname of the Italian World War II fighter aircraft Fiat G.50.
  • C. The Arrow
    The Arrow is the student-run newspaper of Southeast Missouri State University, covering campus news, events, and student life.
  • D. Hawkman
    Hawkman is a DC Comics superhero known for his reincarnated warrior origins, Nth metal wings and weaponry, and long-standing membership in teams like the Justice Society of America.
  • E. Will Scarlet
    Will Scarlet is a legendary member of Robin Hood’s Merry Men, often portrayed as a dashing, hot-headed outlaw skilled with the sword.
  • 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: Arrow
Triple: [Kenneth Arrow, familyName, Arrow]
Generated description
Arrow is a common English surname borne by various individuals, including the influential economist Kenneth Arrow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arrow
Target entity description: Arrow is a common English surname borne by various individuals, including the influential economist Kenneth Arrow.
  • A. Arrow
    Arrow is the English translation of "Freccia," the nickname of the Italian World War II fighter aircraft Fiat G.50.
  • B. Arrow
    Arrow is a popular American superhero television series based on the DC Comics character Green Arrow, known for launching the interconnected "Arrowverse" franchise.
  • C. The Arrow
    The Arrow is the student-run newspaper of Southeast Missouri State University, covering campus news, events, and student life.
  • D. Hawkman
    Hawkman is a DC Comics superhero known for his reincarnated warrior origins, Nth metal wings and weaponry, and long-standing membership in teams like the Justice Society of America.
  • E. Will Scarlet
    Will Scarlet is a legendary member of Robin Hood’s Merry Men, often portrayed as a dashing, hot-headed outlaw skilled with the sword.
  • 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_69c69f3567008190ab01d2ca7b53584a completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9d9c55c8190841f3bf3225c096a completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861b0649c8190b374b5e81f8ba453 completed March 28, 2026, 11:18 p.m.
NEDg Description generation batch_69c86211e4f88190b38bce6441e33b53 completed March 28, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_69c862bb95e881909a60608a5279238d completed March 28, 2026, 11:22 p.m.
Created at: March 27, 2026, 3:53 p.m.