Triple

T31961829
Position Surface form Disambiguated ID Type / Status
Subject Cité Universitaire (Paris) E816059 entity
Predicate hasPart P35 FINISHED
Object Maison des étudiants marocains
Maison des étudiants marocains is a student residence and cultural center in Paris dedicated to hosting and supporting Moroccan students within the Cité Internationale Universitaire.
E1986193 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: Maison des étudiants marocains | Statement: [Cité Universitaire (Paris), hasPart, Maison des étudiants marocains]
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: Maison des étudiants marocains
Triple: [Cité Universitaire (Paris), hasPart, Maison des étudiants marocains]
Generated description
Maison des étudiants marocains is a student residence and cultural center in Paris dedicated to hosting and supporting Moroccan students within the Cité Internationale Universitaire.

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_69f348f4ec708190abbb2a7c3ed58844 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b2e75b088190a60bdfba81feef44 completed May 3, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2eb141f64c8190a13ce224f8435e96 completed June 14, 2026, 1:48 p.m.
NEDg Description generation batch_6a2eb202403881909faf2f1cf6d7e45e completed June 14, 2026, 1:52 p.m.
NED2 Entity disambiguation (via description) batch_6a2eb2c3b12c81908edb48e77352602f completed June 14, 2026, 1:55 p.m.
Created at: May 1, 2026, 12:09 a.m.