Triple

T30945458
Position Surface form Disambiguated ID Type / Status
Subject St Peter's College, Oxford E788377 entity
Predicate foundedAs P364 FINISHED
Object St Peter's Hall
St Peter's Hall was the original name and collegiate foundation that later became St Peter's College, one of the constituent colleges of the University of Oxford.
E1937839 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: St Peter's Hall | Statement: [St Peter's College, Oxford, foundedAs, St Peter's Hall]
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: St Peter's Hall
Triple: [St Peter's College, Oxford, foundedAs, St Peter's Hall]
Generated description
St Peter's Hall was the original name and collegiate foundation that later became St Peter's College, one of the constituent colleges of the University of Oxford.

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_69f224c180f88190ad177372ee02b7e2 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69314c6fc8190ab490fb802592f4b completed May 3, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e47ca0388190a89fd31e19479ea7 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e6c79aa88190862535be33595f23 completed June 10, 2026, 4:23 a.m.
NED2 Entity disambiguation (via description) batch_6a28e75dd5848190ba2f69ced6106bdb completed June 10, 2026, 4:26 a.m.
Created at: April 29, 2026, 8:53 p.m.