Triple

T29518896
Position Surface form Disambiguated ID Type / Status
Subject The Runaway Bus E748874 entity
Predicate starredActor P5563 FINISHED
Object Sam Kydd
Sam Kydd was a prolific British character actor known for his numerous supporting roles in mid-20th-century film and television.
E1870895 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: Sam Kydd | Statement: [The Runaway Bus, starredActor, Sam Kydd]
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: Sam Kydd
Triple: [The Runaway Bus, starredActor, Sam Kydd]
Generated description
Sam Kydd was a prolific British character actor known for his numerous supporting roles in mid-20th-century film and television.

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_69f66c97ee788190a4ef192d3141fa57 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, 4:39 p.m.