Triple

T33579042
Position Surface form Disambiguated ID Type / Status
Subject Muhammadan Anglo-Oriental College E860101 entity
Predicate associatedPerson P2308 FINISHED
Object Theodore Morison
Theodore Morison was a British educationist and administrator known for his influential role in shaping modern higher education for Indian Muslims in the late 19th and early 20th centuries.
E2058002 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: Theodore Morison | Statement: [Muhammadan Anglo-Oriental College, associatedPerson, Theodore Morison]
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: Theodore Morison
Triple: [Muhammadan Anglo-Oriental College, associatedPerson, Theodore Morison]
Generated description
Theodore Morison was a British educationist and administrator known for his influential role in shaping modern higher education for Indian Muslims in the late 19th and early 20th centuries.

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_69f3497d37848190afcbb5ef3f5c7376 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f76e085c81909d71d6f47853cd12 completed May 3, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afe373f88190abc1119522549c35 completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35b1830e288190a2344252b343b93f completed June 19, 2026, 9:15 p.m.
NED2 Entity disambiguation (via description) batch_6a35b23d31408190b8709a5c34347901 completed June 19, 2026, 9:18 p.m.
Created at: May 1, 2026, 1:40 a.m.