Triple

T38156804
Position Surface form Disambiguated ID Type / Status
Subject Hengwrt Manuscript of The Canterbury Tales E952907 entity
Predicate associatedWork P922 FINISHED
Object Man of Law’s Tale
"Man of Law’s Tale" is one of Geoffrey Chaucer’s Canterbury Tales, a narrative in verse that recounts the trials and travels of the virtuous Christian heroine Constance.
E2257167 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: Man of Law’s Tale | Statement: [Hengwrt Manuscript of The Canterbury Tales, associatedWork, Man of Law’s Tale]
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: Man of Law’s Tale
Triple: [Hengwrt Manuscript of The Canterbury Tales, associatedWork, Man of Law’s Tale]
Generated description
"Man of Law’s Tale" is one of Geoffrey Chaucer’s Canterbury Tales, a narrative in verse that recounts the trials and travels of the virtuous Christian heroine Constance.

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_69f76f0a67f4819080c492f61d688fcc completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fc46355fd481908e25ff3d3685c597 completed May 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a417136b0a481908716318213f9130f completed June 28, 2026, 7:08 p.m.
NEDg Description generation batch_6a417212405c8190a2ff740f6d08c3f1 completed June 28, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_6a41728fc1a0819095243c1ef249ace3 completed June 28, 2026, 7:14 p.m.
Created at: May 3, 2026, 4:21 p.m.