Triple

T16963666
Position Surface form Disambiguated ID Type / Status
Subject Division of Aquatic Resources E411490 entity
Predicate shortName P43 FINISHED
Object DAR
DAR is the abbreviated name for the Division of Aquatic Resources, a government body responsible for managing and conserving aquatic ecosystems and resources.
 E1242500 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: DAR | Statement: [Division of Aquatic Resources, shortName, DAR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DAR
Context triple: [Division of Aquatic Resources, shortName, DAR]
  • A. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • B. DARD
    DARD is an organization focused on translating research findings into practical applications and real-world impact.
  • C. DRA
    DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
  • D. DGAR
    DGAR is the abbreviated title for the Director General of Assam Rifles, the senior-most officer commanding India’s Assam Rifles paramilitary force.
  • E. DA
    DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • 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: DAR
Triple: [Division of Aquatic Resources, shortName, DAR]
Generated description
DAR is the abbreviated name for the Division of Aquatic Resources, a government body responsible for managing and conserving aquatic ecosystems and resources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DAR
Target entity description: DAR is the abbreviated name for the Division of Aquatic Resources, a government body responsible for managing and conserving aquatic ecosystems and resources.
  • A. DAR
    DAR is the Philippine government agency responsible for implementing agrarian reform and redistributing agricultural land to farmers.
  • B. DARD
    DARD is an organization focused on translating research findings into practical applications and real-world impact.
  • C. DRA
    DRA is the commonly used abbreviation for the Democratic Republic of Afghanistan, the Soviet-aligned Afghan state that existed from 1978 to 1992.
  • D. DGAR
    DGAR is the abbreviated title for the Director General of Assam Rifles, the senior-most officer commanding India’s Assam Rifles paramilitary force.
  • E. DA
    DA is the commonly used abbreviation for the Defence Academy of the United Kingdom, the institution responsible for advanced education and training of the UK’s armed forces and defence personnel.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d0a1f6308190af5ad171630dacbf completed April 18, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d46cb56481908c2bc6648a12fbcf completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d4f1bfa48190903bedc43ed6db75 completed May 10, 2026, 6:56 p.m.
NED2 Entity disambiguation (via description) batch_6a00d59b96108190a0e55f01529a0b64 completed May 10, 2026, 6:59 p.m.
Created at: April 10, 2026, 5:31 a.m.