Triple

T35780287
Position Surface form Disambiguated ID Type / Status
Subject Faculty of Legal Sciences E1034418 entity
Predicate locatedIn P40 FINISHED
Object Tarragona metropolitan area
The Tarragona metropolitan area is an urban and economic region in Catalonia, Spain, centered on the historic port city of Tarragona and its surrounding municipalities.
E2159971 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: Tarragona metropolitan area | Statement: [Faculty of Legal Sciences, locatedIn, Tarragona 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: Tarragona metropolitan area
Triple: [Faculty of Legal Sciences, locatedIn, Tarragona metropolitan area]
Generated description
The Tarragona metropolitan area is an urban and economic region in Catalonia, Spain, centered on the historic port city of Tarragona and its surrounding municipalities.

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_69f76e14a1e081908eddd57bd6fdb3be completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1feb5a48190bfc05dd6110ef41f completed May 3, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38a4d935988190b0e265c841c29ecf completed June 22, 2026, 2:58 a.m.
NEDg Description generation batch_6a38a6d1b6d481909e1461d8e820059b completed June 22, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_6a38a74cfac08190b4aa29a22d59c192 completed June 22, 2026, 3:09 a.m.
Created at: May 3, 2026, 4:06 p.m.