Triple

T36816635
Position Surface form Disambiguated ID Type / Status
Subject Maks Luburić E909758 entity
Predicate usedAlias P3799 FINISHED
Object Vicente Pérez García
Vicente Pérez García was an alias used by Croatian Ustaše official and World War II war criminal Maks Luburić.
E2284418 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: Vicente Pérez García | Statement: [Maks Luburić, usedAlias, Vicente Pérez García]
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: Vicente Pérez García
Triple: [Maks Luburić, usedAlias, Vicente Pérez García]
Generated description
Vicente Pérez García was an alias used by Croatian Ustaše official and World War II war criminal Maks Luburić.

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_69f76e7dd13c81908c60b05adb49eeb5 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7ca94734c819094bd74a7384d81ce completed May 3, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a438a27783481908df1696aa7f7af5d completed June 30, 2026, 9:19 a.m.
NEDg Description generation batch_6a438b5d9c608190a33ffed9b9ff805e completed June 30, 2026, 9:24 a.m.
NED2 Entity disambiguation (via description) batch_6a438bd204e08190a4ed75eecc35868f completed June 30, 2026, 9:26 a.m.
Created at: May 3, 2026, 4:13 p.m.