Triple

T4446288
Position Surface form Disambiguated ID Type / Status
Subject Østfold E96296 entity
Predicate contains P35 FINISHED
Object Marker E50824 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: Marker | Statement: [Østfold, contains, Marker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marker
Context triple: [Østfold, contains, Marker]
  • A. Marker chosen
    Marker is a rural municipality in Viken county, southeastern Norway, known for its forests, lakes, and location near the Swedish border.
  • B. Marks
    Marks is a surname of English and Jewish origin borne by various notable individuals across fields such as sports, politics, and the arts.
  • 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_69b345415ba481908df738e7174448ba completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b355d1eba08190899d0a3c1684ce4e completed March 13, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b613850eb88190b689a632b0e2b374 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:32 p.m.