Triple

T26672573
Position Surface form Disambiguated ID Type / Status
Subject Mala Rijeka Viaduct E672372 entity
Predicate locatedOnRoute P6309 FINISHED
Object Belgrade–Bar
Belgrade–Bar is a major international railway line connecting the Serbian capital Belgrade with the Montenegrin Adriatic port city of Bar, traversing mountainous terrain and featuring notable engineering works.
E1734209 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: Belgrade–Bar | Statement: [Mala Rijeka Viaduct, locatedOnRoute, Belgrade–Bar]
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: Belgrade–Bar
Triple: [Mala Rijeka Viaduct, locatedOnRoute, Belgrade–Bar]
Generated description
Belgrade–Bar is a major international railway line connecting the Serbian capital Belgrade with the Montenegrin Adriatic port city of Bar, traversing mountainous terrain and featuring notable engineering works.

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_69eecda00a9c8190b2691f4d89db03b6 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6170044f081908403e5e59a52a57b completed May 2, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec52e70c819080f9767f7a481b09 completed May 23, 2026, 6:05 p.m.
NEDg Description generation batch_6a11ed2cc62c8190b582f46a4b2ca426 completed May 23, 2026, 6:08 p.m.
NED2 Entity disambiguation (via description) batch_6a11edac59388190bfa4e3e288b7932e completed May 23, 2026, 6:10 p.m.
Created at: April 27, 2026, 3:13 a.m.