Triple

T35886280
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Kraljevica E1037651 entity
Predicate hasSettlement P1068 FINISHED
Object Križišće
Križišće is a village in Primorje-Gorski Kotar County in western Croatia, situated near the Adriatic coast and administratively associated with the nearby town of Kraljevica.
E2220773 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: Križišće | Statement: [Municipality of Kraljevica, hasSettlement, Križišće]
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: Križišće
Triple: [Municipality of Kraljevica, hasSettlement, Križišće]
Generated description
Križišće is a village in Primorje-Gorski Kotar County in western Croatia, situated near the Adriatic coast and administratively associated with the nearby town of Kraljevica.

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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa0a13d08190a32dd959e5ec09b8 completed May 3, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40510b707c8190bbe38132892df2d2 completed June 27, 2026, 10:39 p.m.
NEDg Description generation batch_6a4052ce8944819089f900342fb74e54 completed June 27, 2026, 10:46 p.m.
NED2 Entity disambiguation (via description) batch_6a405328d6788190a76e76a9b1565310 completed June 27, 2026, 10:48 p.m.
Created at: May 3, 2026, 4:06 p.m.