Triple

T35669306
Position Surface form Disambiguated ID Type / Status
Subject Finnøy Municipality E1030665 entity
Predicate mergedWith P77 FINISHED
Object Rennesøy Municipality
Rennesøy Municipality was a former municipality in Rogaland county, Norway, consisting of several islands north of Stavanger, known for its coastal landscape and later incorporation into a larger municipal unit.
E1030665 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: Rennesøy Municipality | Statement: [Finnøy Municipality, mergedWith, Rennesøy Municipality]
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: Rennesøy Municipality
Triple: [Finnøy Municipality, mergedWith, Rennesøy Municipality]
Generated description
Rennesøy Municipality was a former municipality in Rogaland county, Norway, consisting of several islands north of Stavanger, known for its coastal landscape and later incorporation into a larger municipal unit.

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_69f76e0acfc0819082c8495c2210ce73 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fb10c4881908b12bfceaaf085f1 completed May 3, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a478b16e5108190b39d64aedc14131b completed July 3, 2026, 10:12 a.m.
NEDg Description generation batch_6a478bbcafcc81909b704e95bbede980 completed July 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_6a478c5f2c90819080123b9a583d3c0b completed July 3, 2026, 10:18 a.m.
Created at: May 3, 2026, 4:05 p.m.