Triple

T29520123
Position Surface form Disambiguated ID Type / Status
Subject Circus Circus Enterprises E748908 entity
Predicate foundedBy P104 FINISHED
Object William Pennington
William Pennington was an American casino developer and businessman best known for building and expanding major Las Vegas properties, including Circus Circus.
E1870967 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: William Pennington | Statement: [Circus Circus Enterprises, foundedBy, William Pennington]
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: William Pennington
Triple: [Circus Circus Enterprises, foundedBy, William Pennington]
Generated description
William Pennington was an American casino developer and businessman best known for building and expanding major Las Vegas properties, including Circus Circus.

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_69f0bd461c208190bec20bbf24e02cc5 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c98a0988190a56084c196e39c13 completed May 2, 2026, 9:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a260c2b1e088190b2f5c4c6f49aa440 completed June 8, 2026, 12:26 a.m.
NEDg Description generation batch_6a26101eb69481909e5a27c1fd3791f0 completed June 8, 2026, 12:43 a.m.
NED2 Entity disambiguation (via description) batch_6a26142129608190b8028efd1baf9f50 completed June 8, 2026, 1 a.m.
Created at: April 28, 2026, 4:40 p.m.