Triple

T1360578
Position Surface form Disambiguated ID Type / Status
Subject Tonga E29089 entity
Predicate ISO3166-1Alpha2 P189 FINISHED
Object TO
TO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Kingdom of Tonga.
 E155741 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: TO | Statement: [Tonga, ISO3166-1Alpha2, TO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TO
Context triple: [Tonga, ISO3166-1Alpha2, TO]
  • A. TO
    TO is the IATA airline designator used by Transavia France, a French low-cost carrier.
  • B. OT
    OT is the abbreviation for Organisation Todt, the Nazi-era civil and military engineering group responsible for large-scale construction projects such as the Atlantic Wall.
  • C. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • D. TTO
    TTO is a DARPA office focused on developing and demonstrating high-risk, high-payoff advanced military technologies and systems.
  • E. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • 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: TO
Triple: [Tonga, ISO3166-1Alpha2, TO]
Generated description
TO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Kingdom of Tonga.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TO
Target entity description: TO is the two-letter ISO 3166-1 alpha-2 country code assigned to the Kingdom of Tonga.
  • A. TO
    TO is the IATA airline designator used by Transavia France, a French low-cost carrier.
  • B. OT
    OT is the abbreviation for Organisation Todt, the Nazi-era civil and military engineering group responsible for large-scale construction projects such as the Atlantic Wall.
  • C. TOR
    TOR is the standard three-letter abbreviation used to represent the Toronto Maple Leafs in sports standings, statistics, and media.
  • D. TTO
    TTO is a DARPA office focused on developing and demonstrating high-risk, high-payoff advanced military technologies and systems.
  • E. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • 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_69a498d77abc8190913bf57e5f51d2c4 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c2b156b081909c99ada70a969fc0 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce725fec819085f6de8e6e368aa4 completed March 8, 2026, 1:18 a.m.
NEDg Description generation batch_69accf9ac120819084c21fb7b88c050a completed March 8, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_69accffa9a40819083a3e55a5d83e040 completed March 8, 2026, 1:25 a.m.
Created at: March 1, 2026, 7:56 p.m.