Triple

T2139611
Position Surface form Disambiguated ID Type / Status
Subject Martin Davis E46731 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 Davis, givenName, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Martin
Context triple: [Martin Davis, 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 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 common surname of European origin, widely borne by individuals across many countries and cultures.
  • 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 Davis, 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 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 minor but kind-hearted character in Ernest Hemingway's novella "The Old Man and the Sea," known for helping the old fisherman Santiago.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe025d3c81908bcb33a7ff09eae8 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b1290c8190a08850b428c99a6c completed March 9, 2026, 4:50 a.m.
NEDg Description generation batch_69ae55923b748190bf7a2df3ae94edc8 completed March 9, 2026, 5:07 a.m.
NED2 Entity disambiguation (via description) batch_69ae55fdc32c8190b6ecdc9b23d64cc5 completed March 9, 2026, 5:09 a.m.
Created at: March 4, 2026, 7:44 p.m.