Triple

T35647188
Position Surface form Disambiguated ID Type / Status
Subject Delos Destinations E1030042 entity
Predicate hasKeyPartner P14933 FINISHED
Object Arnold Weber
Arnold Weber is a brilliant but troubled co-founder and visionary engineer behind the lifelike hosts in the fictional theme parks of the TV series "Westworld."
E1567296 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: Arnold Weber | Statement: [Delos Destinations, hasKeyPartner, Arnold Weber]
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: Arnold Weber
Triple: [Delos Destinations, hasKeyPartner, Arnold Weber]
Generated description
Arnold Weber is a brilliant but troubled co-founder and visionary engineer behind the lifelike hosts in the fictional theme parks of the TV series "Westworld."

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_69f76e0938088190a8f199631e97dec3 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79f512e2c819082401a8ce302bda2 completed May 3, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a837fc1db9c8190927dd09eeb1e500e completed Aug. 17, 2026, 9:40 p.m.
NEDg Description generation batch_6a8381a11eb88190bfe33194ee52820e completed Aug. 17, 2026, 9:48 p.m.
NED2 Entity disambiguation (via description) batch_6a83820389d48190a2a5859d0cac671f completed Aug. 17, 2026, 9:49 p.m.
Created at: May 3, 2026, 4:05 p.m.