Triple

T8932943
Position Surface form Disambiguated ID Type / Status
Subject Grand Gedeh County E212700 entity
Predicate hasCountryCode P189 FINISHED
Object LR
LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
 E767831 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: LR | Statement: [Grand Gedeh County, hasCountryCode, LR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LR
Context triple: [Grand Gedeh County, hasCountryCode, LR]
  • A. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • B. LR
    LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • C. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • D. RL
    RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
  • E. RL
    RL is an American R&B singer best known as a member of the group Next and for his smooth vocal contributions to late-1990s and early-2000s R&B hits.
  • 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: LR
Triple: [Grand Gedeh County, hasCountryCode, LR]
Generated description
LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LR
Target entity description: LR is the ISO 3166-1 alpha-2 country code for Liberia, a West African nation on the Atlantic coast.
  • A. LR
    LR is a German vehicle registration code assigned to the Ortenaukreis district in the state of Baden-Württemberg.
  • B. LR
    LR is the stock ticker symbol for Legrand, a global specialist in electrical and digital building infrastructure.
  • C. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • D. RL
    RL is the commonly used acronym for the U.S. Department of Energy’s Richland Operations Office, which oversees environmental cleanup and related activities at the Hanford Site in Washington State.
  • E. RL
    RL is an American R&B singer best known as a member of the group Next and for his smooth vocal contributions to late-1990s and early-2000s R&B hits.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668e5c108190b08f9cd6b4fd4a8b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1d965cc8190bad0a990df318698 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc3b3044c81908631fee4ffe5c25f completed April 3, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_69cfc41fca3081908d8c2515c98283de completed April 3, 2026, 1:43 p.m.
Created at: March 30, 2026, 6:57 p.m.