Triple

T7035547
Position Surface form Disambiguated ID Type / Status
Subject Thomas Bryan Martin E163372 entity
Predicate familyName P18 FINISHED
Object Martin
Martin is a common surname of European origin borne by numerous notable individuals across politics, arts, sciences, and sports.
E214356 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: [Thomas Bryan Martin, familyName, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin
Context triple: [Thomas Bryan Martin, familyName, 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 the central protagonist of the 1991 psychological thriller film "Proof," around whom the story’s exploration of trust, perception, and human connection revolves.
  • C. Martin
    Martin is a pessimistic scholar who serves as one of Candide’s key philosophical foils in Voltaire’s satirical novella "Candide."
  • D. Martin
    Martin was the first name of Martin Luther, a prominent Nazi official who served as a diplomat in the German Foreign Office during the Third Reich.
  • E. Martin
    Martin is a character in Don DeLillo’s novel "Falling Man," which explores the personal and psychological aftermath of the September 11 attacks.
  • 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: [Thomas Bryan Martin, familyName, Martin]
Generated description
Martin is a common surname of European origin borne by numerous notable individuals across politics, arts, sciences, and sports.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Martin
Target entity description: Martin is a common surname of European origin borne by numerous notable individuals across politics, arts, sciences, and sports.
  • A. Martin chosen
    Martin is a common surname of European origin, widely borne by individuals across many countries and cultures.
  • B. Martin
    Martin is a masculine given name of Latin origin, commonly used in many European languages.
  • 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 was the first name of Martin Luther, a prominent Nazi official who served as a diplomat in the German Foreign Office during the Third Reich.
  • 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_69c6885d691c81908cf7d31083113886 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e220508c8190b8950cf38280b8c2 completed March 27, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775a211f88190afe5ed466abcac7a completed March 28, 2026, 6:30 a.m.
NEDg Description generation batch_69c779c064548190bc17a399723f85e7 completed March 28, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_69c77a79e76c8190a42fe57ffc1dc23c completed March 28, 2026, 6:51 a.m.
Created at: March 27, 2026, 2:36 p.m.