Triple

T30978233
Position Surface form Disambiguated ID Type / Status
Subject Franken E789288 entity
Predicate usedBy P260 FINISHED
Object Lex Franken
Lex Franken is an individual whose name appears in association with the use of something attributed to or created by someone named Franken.
E1940052 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: Lex Franken | Statement: [Franken, usedBy, Lex Franken]
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: Lex Franken
Triple: [Franken, usedBy, Lex Franken]
Generated description
Lex Franken is an individual whose name appears in association with the use of something attributed to or created by someone named Franken.

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_69f224c4831c8190be53924ec25a150a completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f693bad310819084426d39ab043d83 completed May 3, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28fbbf83188190a19190898b46769b completed June 10, 2026, 5:53 a.m.
NEDg Description generation batch_6a28fc9284fc8190b27a22bd15360d75 completed June 10, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_6a28fd3b66108190b86217163a2e4e11 completed June 10, 2026, 5:59 a.m.
Created at: April 29, 2026, 8:55 p.m.