Triple

T26611051
Position Surface form Disambiguated ID Type / Status
Subject Petrovec Municipality E667923 entity
Predicate borders P224 FINISHED
Object Studeničani Municipality
Studeničani Municipality is a local administrative unit in North Macedonia situated near the capital Skopje and known for its predominantly rural character and ethnically diverse population.
E1739368 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: Studeničani Municipality | Statement: [Petrovec Municipality, borders, Studeničani 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: Studeničani Municipality
Triple: [Petrovec Municipality, borders, Studeničani Municipality]
Generated description
Studeničani Municipality is a local administrative unit in North Macedonia situated near the capital Skopje and known for its predominantly rural character and ethnically diverse population.

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_69ee9cfe16088190a3dddd68e3c7b1ea completed April 26, 2026, 11:17 p.m.
NER Named-entity recognition batch_69f615a93e3c8190a569c4d548da9900 completed May 2, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe67928c81909b3504e3e3a1bea7 completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff67376c8190a8a6c9fbd5e299d1 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a12001b625881908fc58ccbcbf38b78 completed May 23, 2026, 7:29 p.m.
Created at: April 27, 2026, 2:16 a.m.