Triple

T31081332
Position Surface form Disambiguated ID Type / Status
Subject EURALO Secretariat E792100 entity
Predicate worksWith P398 FINISHED
Object EURALO Chair
The EURALO Chair is the elected leader of the European Regional At-Large Organization within ICANN, responsible for guiding its policy input and representing the interests of European Internet end users.
 E1944023 NE FINISHED

How this triple was built (2 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: EURALO Chair | Statement: [EURALO Secretariat, worksWith, EURALO Chair]
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: EURALO Chair
Triple: [EURALO Secretariat, worksWith, EURALO Chair]
Generated description
The EURALO Chair is the elected leader of the European Regional At-Large Organization within ICANN, responsible for guiding its policy input and representing the interests of European Internet end users.

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_69f224ccdbbc81909b0cdb4cc2d70c7a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f695f9fe7c819084322bf6cdc70a13 completed May 3, 2026, 12:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b291c6c8190bb5181ac803a6ac4 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292b93d7988190b1fe79f38def8b5f completed June 10, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_6a292caa0590819087d6b9d576701697 completed June 10, 2026, 9:21 a.m.
Created at: April 29, 2026, 9:02 p.m.