Triple

T30036928
Position Surface form Disambiguated ID Type / Status
Subject The Tall Texan E763184 entity
Predicate hasCastMember P2308 FINISHED
Object Pat Hogan
Pat Hogan was an American character actor known for his roles in Western films and television during the mid-20th century.
E1902678 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: Pat Hogan | Statement: [The Tall Texan, hasCastMember, Pat Hogan]
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: Pat Hogan
Triple: [The Tall Texan, hasCastMember, Pat Hogan]
Generated description
Pat Hogan was an American character actor known for his roles in Western films and television during the mid-20th century.

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_69f2246fb2b88190acff36bf7975c8f0 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f679d581fc819090781408630f6e27 completed May 2, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27581e24048190bd312c9fad5f913f completed June 9, 2026, 12:02 a.m.
NEDg Description generation batch_6a275a4311f08190b067b8c94e48d019 completed June 9, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_6a275aeeed3c8190ba20d38ec0af1c74 completed June 9, 2026, 12:14 a.m.
Created at: April 29, 2026, 6:51 p.m.