Triple

T18574364
Position Surface form Disambiguated ID Type / Status
Subject Snowden leaks E453947 entity
Predicate approximateDocumentCount P132645 FINISHED
Object thousands of documents LITERAL 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: thousands of documents | Statement: [Snowden leaks, approximateDocumentCount, thousands of documents]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: approximateDocumentCount
Context triple: [Snowden leaks, approximateDocumentCount, thousands of documents]
  • A. lapCountApproximate
    Indicates that the recorded number of laps is an estimate rather than an exact, precise count.
  • B. hasApproximateMemberCount
    Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
  • C. hasApproximateBrickCount
    Indicates that an entity is associated with an estimated or non-exact number of bricks.
  • D. hasApproximateEntryCount
    Indicates that an entity is associated with a number representing an estimated or non-exact count of its entries.
  • E. mineCountApproximate
    Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
  • F. None of above. chosen

Provenance (4 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_69d8d38974308190a9174430ef256b73 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543c8c0608190afc99235006bf87f completed April 19, 2026, 9:06 p.m.
PD Predicate disambiguation batch_69e478c98d4c81909d37a0e72c6e7bd0 completed April 19, 2026, 6:40 a.m.
PDg Predicate description generation batch_69e484121cd48190bf583b4c94636a30 completed April 19, 2026, 7:28 a.m.
Created at: April 10, 2026, 11:43 a.m.