Triple

T11325119
Position Surface form Disambiguated ID Type / Status
Subject Serris E268191 entity
Predicate countryCode P208 FINISHED
Object FR
FR is the ISO 3166-1 alpha-2 country code for France, a major European nation known for its rich culture, history, and global influence.
E919231 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: FR | Statement: [Serris, countryCode, FR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FR
Context triple: [Serris, countryCode, FR]
  • A. FR
    FR is the Swiss vehicle registration code for the canton of Fribourg.
  • B. FR
    FR is the vehicle registration code for the Freiburg im Breisgau district in the German state of Baden-Württemberg.
  • C. FR
    FR is the IATA airline designator used to identify Ryanair flights.
  • D. FR-EE
    FR-EE is an international architecture and design firm known for its innovative, futuristic projects and urban-scale developments led by Mexican architect Fernando Romero.
  • E. French
    French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
  • 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: FR
Triple: [Serris, countryCode, FR]
Generated description
FR is the ISO 3166-1 alpha-2 country code for France, a major European nation known for its rich culture, history, and global influence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: FR
Target entity description: FR is the ISO 3166-1 alpha-2 country code for France, a major European nation known for its rich culture, history, and global influence.
  • A. FR
    FR is the IATA airline designator used to identify Ryanair flights.
  • B. FR
    FR is the Swiss vehicle registration code for the canton of Fribourg.
  • C. FR
    FR is the vehicle registration code for the Freiburg im Breisgau district in the German state of Baden-Württemberg.
  • D. FR-EE
    FR-EE is an international architecture and design firm known for its innovative, futuristic projects and urban-scale developments led by Mexican architect Fernando Romero.
  • E. French
    French is a Romance language that evolved from Latin and is now spoken worldwide as both a native and official language in many countries.
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9e122e48190b3f890de8d561480 completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525fb8d74819089d1505d1f0f116c completed April 19, 2026, 6:59 p.m.
NEDg Description generation batch_69e52c82b6108190aec9b6e9d726f803 completed April 19, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_69e531c2a4b88190bb1efd57536bae9a completed April 19, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:32 p.m.