Triple

T11024560
Position Surface form Disambiguated ID Type / Status
Subject Wallis (ʻUvea) E260581 entity
Predicate ISOCode P208 FINISHED
Object WF-WAL
WF-WAL is the ISO 3166-2 subdivision code assigned to Wallis (ʻUvea), one of the main island groups of the French overseas collectivity of Wallis and Futuna in the South Pacific.
 E900466 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: WF-WAL | Statement: [Wallis (ʻUvea), ISOCode, WF-WAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WF-WAL
Context triple: [Wallis (ʻUvea), ISOCode, WF-WAL]
  • A. WAL
    WAL is the official FIFA country code used to represent the Wales national football team in international competitions and records.
  • B. WAL
    WAL is the National Rail station code for Walton-on-Thames railway station in Surrey, England.
  • C. WF
    WF is the common abbreviation for Windows Workflow Foundation, a Microsoft technology for building workflow-enabled applications within the .NET framework.
  • D. WF
    WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
  • E. WFF
    WFF is the National Rail station code for Whifflet railway station in North Lanarkshire, Scotland.
  • 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: WF-WAL
Triple: [Wallis (ʻUvea), ISOCode, WF-WAL]
Generated description
WF-WAL is the ISO 3166-2 subdivision code assigned to Wallis (ʻUvea), one of the main island groups of the French overseas collectivity of Wallis and Futuna in the South Pacific.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WF-WAL
Target entity description: WF-WAL is the ISO 3166-2 subdivision code assigned to Wallis (ʻUvea), one of the main island groups of the French overseas collectivity of Wallis and Futuna in the South Pacific.
  • A. WAL
    WAL is the official FIFA country code used to represent the Wales national football team in international competitions and records.
  • B. WAL
    WAL is the National Rail station code for Walton-on-Thames railway station in Surrey, England.
  • C. WF
    WF is the common abbreviation for Windows Workflow Foundation, a Microsoft technology for building workflow-enabled applications within the .NET framework.
  • D. WF
    WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
  • E. WFF
    WFF is the National Rail station code for Whifflet railway station in North Lanarkshire, Scotland.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797bf78a48190a37b423812827d4e completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3750917d481909e73de0bfae27827 completed April 18, 2026, 12:11 p.m.
NEDg Description generation batch_69e37ab860f48190808ba0076cfa9c98 completed April 18, 2026, 12:36 p.m.
NED2 Entity disambiguation (via description) batch_69e3864dd0d48190b3fd81381f5d7418 completed April 18, 2026, 1:25 p.m.
Created at: April 8, 2026, 9:25 p.m.