Triple

T6416130
Position Surface form Disambiguated ID Type / Status
Subject Guam Economic Development Authority E127832 entity
Predicate shortName P43 FINISHED
Object GEDA
GEDA is the Guam Economic Development Authority, a government agency that promotes economic growth, investment, and business development in Guam.
 E592425 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: GEDA | Statement: [Guam Economic Development Authority, shortName, GEDA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GEDA
Context triple: [Guam Economic Development Authority, shortName, GEDA]
  • A. GDA
    GDA is a Polish vehicle registration code assigned to cars registered in the Pomeranian Voivodeship, specifically associated with the Gdańsk area.
  • B. GDAE
    GDAE (the Global Development and Environment Institute at Tufts University) is a research center focused on interdisciplinary studies of economics, environment, and social justice.
  • C. EGDC
    EGDC is the ICAO airport code for RM Chivenor, a Royal Marines military airfield in Devon, England.
  • D. GDN
    GDN is the vehicle registration code assigned to motor vehicles registered in the Pomeranian Voivodeship of Poland.
  • E. EGA
    EGA (Éléments de Géométrie Algébrique) is Alexander Grothendieck’s foundational multi-volume work that rigorously reformulated algebraic geometry using the language of schemes and sheaf theory.
  • 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: GEDA
Triple: [Guam Economic Development Authority, shortName, GEDA]
Generated description
GEDA is the Guam Economic Development Authority, a government agency that promotes economic growth, investment, and business development in Guam.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GEDA
Target entity description: GEDA is the Guam Economic Development Authority, a government agency that promotes economic growth, investment, and business development in Guam.
  • A. GDA
    GDA is a Polish vehicle registration code assigned to cars registered in the Pomeranian Voivodeship, specifically associated with the Gdańsk area.
  • B. GDAE
    GDAE (the Global Development and Environment Institute at Tufts University) is a research center focused on interdisciplinary studies of economics, environment, and social justice.
  • C. EGDC
    EGDC is the ICAO airport code for RM Chivenor, a Royal Marines military airfield in Devon, England.
  • D. GDN
    GDN is the vehicle registration code assigned to motor vehicles registered in the Pomeranian Voivodeship of Poland.
  • E. EGA
    EGA (Éléments de Géométrie Algébrique) is Alexander Grothendieck’s foundational multi-volume work that rigorously reformulated algebraic geometry using the language of schemes and sheaf theory.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068e89c2c81909eeedc234e8ccde2 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640caaed881908ff9863b1b792ebc completed March 27, 2026, 8:33 a.m.
NEDg Description generation batch_69c641d6024c8190996aae40851a3b73 completed March 27, 2026, 8:37 a.m.
NED2 Entity disambiguation (via description) batch_69c6425e0a348190bc1eb90eb8c00597 completed March 27, 2026, 8:39 a.m.
Created at: March 22, 2026, 4:42 p.m.