Triple

T24240459
Position Surface form Disambiguated ID Type / Status
Subject A Canterbury Tale E603207 entity
Predicate mainCharacter P1183 FINISHED
Object Thomas Colpeper
Thomas Colpeper is a central character in the 1944 British film "A Canterbury Tale," portrayed as an eccentric local magistrate whose controversial actions and deep reverence for English rural traditions drive much of the story’s moral and spiritual exploration.
E1624743 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: Thomas Colpeper | Statement: [A Canterbury Tale, mainCharacter, Thomas Colpeper]
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: Thomas Colpeper
Triple: [A Canterbury Tale, mainCharacter, Thomas Colpeper]
Generated description
Thomas Colpeper is a central character in the 1944 British film "A Canterbury Tale," portrayed as an eccentric local magistrate whose controversial actions and deep reverence for English rural traditions drive much of the story’s moral and spiritual exploration.

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_69e2953f631c819097cbb421046bd417 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f28a9f812c81909dba8fbb54d8985c completed April 29, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd32123481908440a2c869ba3f25 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbf5e704c8190b92cf2c13cce3539 completed May 22, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc0032df4819094fb2a552bcd76a7 completed May 22, 2026, 2:31 a.m.
Created at: April 18, 2026, 12:03 a.m.