Triple

T15732792
Position Surface form Disambiguated ID Type / Status
Subject Martin Peretz E381385 entity
Predicate givenName P17 FINISHED
Object Martin
Martin is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
E223140 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: Martin | Statement: [Martin Peretz, givenName, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin
Context triple: [Martin Peretz, givenName, Martin]
  • A. Martin
    Martin is a minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • B. Martin
    Martin is a pessimistic scholar who serves as one of Candide’s key philosophical foils in Voltaire’s satirical novella "Candide."
  • C. Martin
    Martin is a character in Don DeLillo’s novel "Falling Man," which explores the personal and psychological aftermath of the September 11 attacks.
  • D. Martin
    Martin is a brand best known for its Martin N-20 classical acoustic guitar, famously associated with Willie Nelson’s instrument “Trigger.”
  • E. Martin
    Martin is a fictional character from the television comedy series "Blunt Talk."
  • 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: Martin
Triple: [Martin Peretz, givenName, Martin]
Generated description
Martin is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Martin
Target entity description: Martin is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
  • A. Martin chosen
    Martin is a masculine given name of Latin origin, commonly used in many European languages.
  • B. Martin
    Martin is a common surname of European origin, widely borne by individuals across many countries and cultures.
  • C. Martin
    Martin is the given name of Martin Luther King Jr., the prominent American civil rights leader and Baptist minister who advocated nonviolent resistance to racial segregation.
  • D. Martin
    Martin is the given name of Martin Luther the Younger, a 16th-century German theologian and the son of Protestant Reformation leader Martin Luther.
  • E. Martin
    Martin is the given name of Martin Delany, a prominent 19th-century African American abolitionist, writer, and one of the first Black field officers in the U.S. Army.
  • F. None of above.

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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd3614481908b2694b1d3550058 completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82fed7888190b45f28ac91e0079e completed May 9, 2026, 6:54 p.m.
NEDg Description generation batch_69ff83b7a534819090e24491579376c3 completed May 9, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69ff844fa00c8190a47eb46394db097b completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.