Triple

T31094085
Position Surface form Disambiguated ID Type / Status
Subject Sabrina Fair E792477 entity
Predicate titleReference P12689 FINISHED
Object John Milton’s masque Comus
John Milton’s masque *Comus* is a 17th-century allegorical drama in verse that explores themes of virtue, temptation, and chastity through a mythic woodland encounter with an enchanter.
E1945500 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: John Milton’s masque Comus | Statement: [Sabrina Fair, titleReference, John Milton’s masque Comus]
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: John Milton’s masque Comus
Triple: [Sabrina Fair, titleReference, John Milton’s masque Comus]
Generated description
John Milton’s masque *Comus* is a 17th-century allegorical drama in verse that explores themes of virtue, temptation, and chastity through a mythic woodland encounter with an enchanter.

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_69f224cf157c81909e2d2bd88c9282c3 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6966d30d08190b058c5d689eae3da completed May 3, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a292b33b42c8190aac82304302b56f0 completed June 10, 2026, 9:15 a.m.
NEDg Description generation batch_6a292f34ad0c8190aaa7106924983df3 completed June 10, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a293066274c8190b496b6f863917942 completed June 10, 2026, 9:37 a.m.
Created at: April 29, 2026, 9:03 p.m.