Triple

T17128054
Position Surface form Disambiguated ID Type / Status
Subject Princess Likelike E415649 entity
Predicate givenName P17 FINISHED
Object Miriam
Miriam is the given first name of Princess Likelike, a Hawaiian royal figure of the 19th century.
E1251404 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: Miriam | Statement: [Princess Likelike, givenName, Miriam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miriam
Context triple: [Princess Likelike, givenName, Miriam]
  • A. Miriam
    Miriam is a central fictional character in Nathaniel Hawthorne’s novel "The Marble Faun," portrayed as a mysterious and artistically gifted woman with a troubled past.
  • B. Miriam
    Miriam "Midge" Maisel is the quick-witted 1950s New York housewife-turned-stand-up-comedian who stars as the protagonist of the television series "The Marvelous Mrs. Maisel."
  • C. Miriam
    Miriam is a prominent biblical figure known as the sister of Moses and Aaron and as a prophetess during the Exodus of the Israelites from Egypt.
  • D. Miriam
    Miriam is a fictional character from the British dark comedy television series "The Life and Times of Vivienne Vyle."
  • E. Miriam
    Miriam is the birth name of American country music singer and songwriter Jessi Colter.
  • 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: Miriam
Triple: [Princess Likelike, givenName, Miriam]
Generated description
Miriam is the given first name of Princess Likelike, a Hawaiian royal figure of the 19th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Miriam
Target entity description: Miriam is the given first name of Princess Likelike, a Hawaiian royal figure of the 19th century.
  • A. Miriam
    Miriam is a prominent biblical figure known as the sister of Moses and Aaron and as a prophetess during the Exodus of the Israelites from Egypt.
  • B. Miriam
    Miriam is the birth name of American country music singer and songwriter Jessi Colter.
  • C. Miriam
    Miriam is a central fictional character in Nathaniel Hawthorne’s novel "The Marble Faun," portrayed as a mysterious and artistically gifted woman with a troubled past.
  • D. Miriam
    Miriam is a key supporting character in Lew Wallace's novel "Ben-Hur: A Tale of the Christ," serving as Judah Ben-Hur's mother and a central figure in his personal trials and motivations.
  • E. Miriam
    Miriam is a key member of the underground resistance group known as the Fishes in the dystopian world of "Children of Men."
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f0285a408190ae5e4c4679c07fbf completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a145e7481909242aab69baeb7a0 completed May 11, 2026, 2:08 a.m.
NEDg Description generation batch_6a013a8e69388190b8d48d70a28e99bd completed May 11, 2026, 2:10 a.m.
NED2 Entity disambiguation (via description) batch_6a013b6824888190853cf36548507e1b completed May 11, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:36 a.m.