Triple

T7484352
Position Surface form Disambiguated ID Type / Status
Subject Division of Environmental Assessment and Restoration E176841 entity
Predicate abbreviation P43 FINISHED
Object DEAR
DEAR is a governmental environmental division focused on assessing, monitoring, and restoring natural ecosystems and resources.
E667058 NE FINISHED

How this triple was built (4 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: DEAR | Statement: [Division of Environmental Assessment and Restoration, abbreviation, DEAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DEAR
Context triple: [Division of Environmental Assessment and Restoration, abbreviation, DEAR]
  • A. Dearest
    Dearest is a character appearing in the 1921 silent film adaptation of "Little Lord Fauntleroy."
  • B. Dear John
    Dear John is an American sitcom that aired from 1988 to 1992, starring Judd Hirsch as a recently divorced man navigating single life and friendships in a New York City support group.
  • C. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • D. De
    De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
  • E. DEE
    DEE is the IATA airport code for Yuzhno-Kurilsk Mendeleyevo Airport, which serves the town of Yuzhno-Kurilsk in Russia’s Kuril Islands.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DEAR
Triple: [Division of Environmental Assessment and Restoration, abbreviation, DEAR]
Generated description
DEAR is a governmental environmental division focused on assessing, monitoring, and restoring natural ecosystems and resources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DEAR
Target entity description: DEAR is a governmental environmental division focused on assessing, monitoring, and restoring natural ecosystems and resources.
  • A. Dearest
    Dearest is a character appearing in the 1921 silent film adaptation of "Little Lord Fauntleroy."
  • B. Dear John
    Dear John is an American sitcom that aired from 1988 to 1992, starring Judd Hirsch as a recently divorced man navigating single life and friendships in a New York City support group.
  • C. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • D. De
    De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
  • E. DEE
    DEE is the IATA airport code for Yuzhno-Kurilsk Mendeleyevo Airport, which serves the town of Yuzhno-Kurilsk in Russia’s Kuril Islands.
  • F. None of above. chosen

Provenance (5 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f53a6bc081909f4b9cd7cdacf045 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8349d83cc8190af98c3212e28e913 completed March 28, 2026, 8:05 p.m.
NEDg Description generation batch_69c835916e948190ad5789e4611f8842 completed March 28, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_69c83635c7888190834f02e7ea0f1ab5 completed March 28, 2026, 8:12 p.m.
Created at: March 27, 2026, 3:42 p.m.