Triple

T24333105
Position Surface form Disambiguated ID Type / Status
Subject Saint-Denis, Réunion E613300 entity
Predicate isSeatOf P62 FINISHED
Object Prefecture of Réunion
The Prefecture of Réunion is the central administrative authority representing the French state on the island of Réunion, overseeing government services and state functions from its seat in Saint-Denis.
E1706298 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: Prefecture of Réunion | Statement: [Saint-Denis, Réunion, isSeatOf, Prefecture of Réunion]
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: Prefecture of Réunion
Triple: [Saint-Denis, Réunion, isSeatOf, Prefecture of Réunion]
Generated description
The Prefecture of Réunion is the central administrative authority representing the French state on the island of Réunion, overseeing government services and state functions from its seat in Saint-Denis.

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_69e2d7db6d5c819091194918157a7c1f completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f381b08190b529a765a5d5e89b completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a111ad7daf481908dd4668784a83be0 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111ba170c881908916feb646df7338 completed May 23, 2026, 3:14 a.m.
NED2 Entity disambiguation (via description) batch_6a111c1129588190918ec8f98cad6fd4 completed May 23, 2026, 3:16 a.m.
Created at: April 18, 2026, 1:56 a.m.