Triple

T25714755
Position Surface form Disambiguated ID Type / Status
Subject The Pale Horse (TV series) E644829 entity
Predicate featuresCharacter P626 FINISHED
Object Mark Easterbrook
Mark Easterbrook is the central protagonist of Agatha Christie's mystery "The Pale Horse," depicted as an ordinary man drawn into investigating a series of sinister deaths linked to a supposedly supernatural inn.
E1697894 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: Mark Easterbrook | Statement: [The Pale Horse (TV series), featuresCharacter, Mark Easterbrook]
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: Mark Easterbrook
Triple: [The Pale Horse (TV series), featuresCharacter, Mark Easterbrook]
Generated description
Mark Easterbrook is the central protagonist of Agatha Christie's mystery "The Pale Horse," depicted as an ordinary man drawn into investigating a series of sinister deaths linked to a supposedly supernatural inn.

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_69e77e8476fc8190bd5e9d05b89fad0a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fc610aac81909ee4722dcfcca67d completed May 2, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9ff3df4819099b40aaf43cf83b6 completed May 22, 2026, 10:34 p.m.
NEDg Description generation batch_6a10db772c408190875e23a357eb75d9 completed May 22, 2026, 10:40 p.m.
NED2 Entity disambiguation (via description) batch_6a10dc2096b881909e87c9cc277bc831 completed May 22, 2026, 10:43 p.m.
Created at: April 21, 2026, 9:38 p.m.