Triple

T10975510
Position Surface form Disambiguated ID Type / Status
Subject Mark Williams E259359 entity
Predicate givenName P17 FINISHED
Object Mark E161211 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 Williams, givenName, Mark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark
Context triple: [Mark Williams, givenName, Mark]
  • A. Mark
    The Mark was the basic unit of currency used in Germany during various historical periods, including the era of the Papiermark.
  • B. Mark
    Mark is a quirky, music-obsessed employee at the independent record store in the 1995 cult film "Empire Records," known for his goofy charm and laid-back attitude.
  • C. Mark
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • D. Mark
    Mark is one of the four canonical Gospels in the New Testament, traditionally attributed to John Mark and known for its concise, fast-paced account of the life, ministry, death, and resurrection of Jesus Christ.
  • E. Mark chosen
    Mark is a common masculine given name of Latin origin, derived from Marcus and historically associated with figures such as the evangelist Saint Mark.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771f4e888819097433271a2f45ff3 completed April 9, 2026, 9:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7aeb66c8190b9d18642b2ad2ea0 completed April 18, 2026, 1 a.m.
Created at: April 8, 2026, 9:24 p.m.