Triple

T26813993
Position Surface form Disambiguated ID Type / Status
Subject LRIA E672073 entity
Predicate servesArea P82 FINISHED
Object Iași metropolitan area
The Iași metropolitan area is an urban agglomeration in northeastern Romania centered on the city of Iași, encompassing surrounding communes for coordinated regional development and services.
E1752761 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: Iași metropolitan area | Statement: [LRIA, servesArea, Iași metropolitan area]
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: Iași metropolitan area
Triple: [LRIA, servesArea, Iași metropolitan area]
Generated description
The Iași metropolitan area is an urban agglomeration in northeastern Romania centered on the city of Iași, encompassing surrounding communes for coordinated regional development and services.

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_69eeb3225a3c8190aaf6746efeded2f3 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f61a83c8ec8190ba1f49371889e547 completed May 2, 2026, 3:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a123a9c25bc8190bc4d1a6d69fa2677 completed May 23, 2026, 11:39 p.m.
NEDg Description generation batch_6a123ba9aea081909f20ff78ab91747e completed May 23, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a123c56268c81909d0e71dad0aeab01 completed May 23, 2026, 11:46 p.m.
Created at: April 27, 2026, 4:31 a.m.