Triple

T787776
Position Surface form Disambiguated ID Type / Status
Subject Mark Kac E16842 entity
Predicate givenName P17 FINISHED
Object Mark E1581 NE FINISHED

How this triple was built (2 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: Mark | Statement: [Mark Kac, givenName, Mark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark
Context triple: [Mark Kac, givenName, Mark]
  • A. Mark chosen
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • B. Marc
    Marc is the given name of Marc Andreessen, the influential American entrepreneur, software engineer, and venture capitalist known for co-creating the Mosaic web browser and co-founding Netscape and Andreessen Horowitz.
  • C. Marks
    Marks is a surname of English and Jewish origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • D. Jonathan
    Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
  • E. Jeremy
    Jeremy is one of the central male protagonists in the romantic comedy film "Think Like a Man," which follows a group of men whose relationships are upended when their partners start using advice from Steve Harvey’s dating book.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a78171908190a38a70274bfbebf9 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a67efd612481909580fbef3605dcbc completed March 3, 2026, 6:26 a.m.
Created at: March 1, 2026, 7:38 p.m.