Triple

T1572596
Position Surface form Disambiguated ID Type / Status
Subject Prince George’s County Fire/EMS Department E33573 entity
Predicate hasAbbreviation P43 FINISHED
Object PGFD
PGFD is the fire and emergency medical services agency serving Prince George’s County, Maryland.
E179513 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: PGFD | Statement: [Prince George’s County Fire/EMS Department, hasAbbreviation, PGFD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PGFD
Context triple: [Prince George’s County Fire/EMS Department, hasAbbreviation, PGFD]
  • A. AGFD
    AGFD is the American Chemical Society’s Division of Agricultural and Food Chemistry, focusing on the chemistry of agriculture, food, and related products.
  • B. GDF
    GDF is the Global Drug Facility, an international mechanism that supplies quality-assured medicines and diagnostics to support tuberculosis control and treatment programs worldwide.
  • C. GDPFS
    GDPFS is the World Meteorological Organization’s global system for collecting, processing, and sharing meteorological data and forecasts among national and international centers.
  • D. GF
    GF is the two-letter ISO 3166-1 alpha-2 country code assigned to French Guiana.
  • E. GAFI
    GAFI is the French acronym for the Financial Action Task Force, an intergovernmental body that sets global standards to combat money laundering, terrorist financing, and related financial crimes.
  • 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: PGFD
Triple: [Prince George’s County Fire/EMS Department, hasAbbreviation, PGFD]
Generated description
PGFD is the fire and emergency medical services agency serving Prince George’s County, Maryland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: PGFD
Target entity description: PGFD is the fire and emergency medical services agency serving Prince George’s County, Maryland.
  • A. AGFD
    AGFD is the American Chemical Society’s Division of Agricultural and Food Chemistry, focusing on the chemistry of agriculture, food, and related products.
  • B. GDF
    GDF is the Global Drug Facility, an international mechanism that supplies quality-assured medicines and diagnostics to support tuberculosis control and treatment programs worldwide.
  • C. GDPFS
    GDPFS is the World Meteorological Organization’s global system for collecting, processing, and sharing meteorological data and forecasts among national and international centers.
  • D. GF
    GF is the two-letter ISO 3166-1 alpha-2 country code assigned to French Guiana.
  • E. GAFI
    GAFI is the French acronym for the Financial Action Task Force, an intergovernmental body that sets global standards to combat money laundering, terrorist financing, and related financial crimes.
  • 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_69a885f11b048190935025a035302715 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908bb9c648190933fd19bcc1cb9a4 completed March 5, 2026, 4:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad4028bc5881909dbe847229dd63bb completed March 8, 2026, 9:23 a.m.
NEDg Description generation batch_69ad41930d208190b34531e3f35fa58b completed March 8, 2026, 9:29 a.m.
NED2 Entity disambiguation (via description) batch_69ad422752348190b42ebc3781a6e8a5 completed March 8, 2026, 9:32 a.m.
Created at: March 4, 2026, 7:27 p.m.