Triple

T3069174
Position Surface form Disambiguated ID Type / Status
Subject Saratov Oblast E62177 entity
Predicate containsCity P294 FINISHED
Object Marks E87869 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: Marks | Statement: [Saratov Oblast, containsCity, Marks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marks
Context triple: [Saratov Oblast, containsCity, Marks]
  • A. Marks chosen
    Marks is a surname of English and Jewish origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • B. Mark
    Mark is a common masculine given name of Latin origin, derived from Marcus and historically associated with figures such as the evangelist Saint Mark.
  • C. Mark
    Mark is the given name of Mark Zuckerberg, the American technology entrepreneur and co-founder of Facebook.
  • D. Mark
    Mark is a punctuation symbol used in writing systems, including those that employ the Cyrillic Extended-B Unicode block.
  • E. 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.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0ffcc208190962cc9edcbf43c31 completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f87bec6c8190ae928fc7c4467859 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:02 p.m.