Triple

T366121
Position Surface form Disambiguated ID Type / Status
Subject The Old Man and the Sea E7962 entity
Predicate containsCharacter P5716 FINISHED
Object 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.
 E67629 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: [The Old Man and the Sea, containsCharacter, Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Martin
Context triple: [The Old Man and the Sea, containsCharacter, Martin]
  • A. 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.
  • B. James
    James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
  • C. David
    David is a common given name and surname of Hebrew origin, widely used across many cultures and historically associated with the biblical King David.
  • D. David
    David is the middle name of Dwight D. Eisenhower, the 34th president of the United States and Supreme Allied Commander in Europe during World War II.
  • E. David
    David is a major city in western Panama and the capital of Chiriquí Province.
  • 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: [The Old Man and the Sea, containsCharacter, Martin]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Martin
Target entity description: 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.
  • A. 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.
  • B. James
    James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
  • C. David
    David is a common given name and surname of Hebrew origin, widely used across many cultures and historically associated with the biblical King David.
  • D. David
    David is the middle name of Dwight D. Eisenhower, the 34th president of the United States and Supreme Allied Commander in Europe during World War II.
  • E. David
    David is a major city in western Panama and the capital of Chiriquí Province.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebe7d4d0819083daeb7686ae1914 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc562bc08190b5f1a6f143bd13d1 completed March 1, 2026, 11:31 p.m.
NEDg Description generation batch_69a4cd4fdd048190a0717e884a2a0d6d completed March 1, 2026, 11:35 p.m.
NED2 Entity disambiguation (via description) batch_69a4cdb9bc44819086cff5102a0ce7fd completed March 1, 2026, 11:37 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.