Triple

T2242570
Position Surface form Disambiguated ID Type / Status
Subject Emissions Gap Report E49429 entity
Predicate abbreviation P43 FINISHED
Object EGR
EGR is the commonly used abbreviation for the United Nations Environment Programme’s annual Emissions Gap Report, which assesses the difference between projected greenhouse gas emissions and levels consistent with global climate goals.
 E247826 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: EGR | Statement: [Emissions Gap Report, abbreviation, EGR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EGR
Context triple: [Emissions Gap Report, abbreviation, EGR]
  • A. EG
    EG is the standard abbreviation for the Egmont Group, an international network of Financial Intelligence Units that collaborates to combat money laundering and terrorist financing.
  • B. ER3
    ER3 is the IATA aircraft type code used to designate the Embraer ERJ 135 regional jet.
  • C. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • D. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • E. ER
    ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
  • 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: EGR
Triple: [Emissions Gap Report, abbreviation, EGR]
Generated description
EGR is the commonly used abbreviation for the United Nations Environment Programme’s annual Emissions Gap Report, which assesses the difference between projected greenhouse gas emissions and levels consistent with global climate goals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EGR
Target entity description: EGR is the commonly used abbreviation for the United Nations Environment Programme’s annual Emissions Gap Report, which assesses the difference between projected greenhouse gas emissions and levels consistent with global climate goals.
  • A. EG
    EG is the standard abbreviation for the Egmont Group, an international network of Financial Intelligence Units that collaborates to combat money laundering and terrorist financing.
  • B. ER3
    ER3 is the IATA aircraft type code used to designate the Embraer ERJ 135 regional jet.
  • C. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • D. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • E. ER
    ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
  • 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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0c017548190a71fb4a0e2a8189f completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b0eef98819083bede32490cba7e completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6bbccdb08190a73fd20a110219d9 completed March 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c3d07a08190a6221a33fd02f73e completed March 9, 2026, 6:44 a.m.
Created at: March 4, 2026, 7:47 p.m.