Triple

T14592640
Position Surface form Disambiguated ID Type / Status
Subject RGS-IBG E342480 entity
Predicate publishes P80 FINISHED
Object Geo: Geography and Environment E1108929 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: Geo: Geography and Environment | Statement: [RGS-IBG, publishes, Geo: Geography and Environment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geo: Geography and Environment
Context triple: [RGS-IBG, publishes, Geo: Geography and Environment]
  • A. Geo: Geography and Environment chosen
    Geo: Geography and Environment is a peer-reviewed academic journal focusing on research in geography and environmental studies.
  • B. Geography III
    Geography III is a 1976 poetry collection by American poet Elizabeth Bishop, noted for its precise language, autobiographical elements, and exploration of geography, memory, and perception.
  • C. Geography 2050
    Geography 2050 is a forward-looking conference series focused on the future of our planet’s geography, bringing together experts to explore long-term global trends and challenges.
  • D. Geo
    Geo is a short form of the given name Georges, often used as an informal or familiar nickname.
  • E. Geo
    Geo was a defunct General Motors automobile brand from the late 1980s and 1990s that specialized in small, economy cars often built in partnership with foreign manufacturers.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb43480d8819084a707e56da2c237 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda918542c819099646943be59dd04 completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:24 a.m.