Triple

T23702693
Position Surface form Disambiguated ID Type / Status
Subject Killing Gunther E585635 entity
Predicate starring P1507 FINISHED
Object Ryan Gaul
Ryan Gaul is an American comedic actor known for his work in film and television, often appearing in offbeat and satirical roles.
E1633451 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: Ryan Gaul | Statement: [Killing Gunther, starring, Ryan Gaul]
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: Ryan Gaul
Triple: [Killing Gunther, starring, Ryan Gaul]
Generated description
Ryan Gaul is an American comedic actor known for his work in film and television, often appearing in offbeat and satirical roles.

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_69e24904bd508190abfcb74855de2918 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b684e0a88190b7edeb102585ae9d completed April 29, 2026, 7:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe3314a1481909e285597b6722c97 completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe43199a48190b5be3ede9c40a0e7 completed May 22, 2026, 5:05 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe4c43ce8819095d62058b4b2cfdd completed May 22, 2026, 5:08 a.m.
Created at: April 17, 2026, 6:53 p.m.