Triple
T9332401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bod |
E224554
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Thomas Bodley |
E224553
|
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 Bodley | Statement: [The Bod, namedAfter, Thomas Bodley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Bodley Context triple: [The Bod, namedAfter, Thomas Bodley]
-
A.
Thomas Bodley
chosen
Thomas Bodley was an English diplomat and scholar best known for refounding and endowing the Bodleian Library at the University of Oxford in the early 17th century.
-
B.
Sir Robert Cotton
Sir Robert Cotton was an English antiquarian and politician best known for founding the Cotton Library, one of the most important collections of medieval manuscripts in Britain.
-
C.
Nicholas Bacon
Nicholas Bacon was a prominent 16th-century English lawyer and statesman who served as Lord Keeper of the Great Seal under Queen Elizabeth I.
-
D.
Sir John Gresham
Sir John Gresham was a 16th-century English merchant and Lord Mayor of London who is best known for establishing the historic Gresham's School in Norfolk.
-
E.
Robert Barnes
Robert Barnes was a prominent St. Louis businessman and philanthropist whose contributions to healthcare led to a major hospital being named in his honor.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37afceb88190ad7ffbc7b47a1caa |
completed | April 1, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0f3b37b408190957c371233d8a3bd |
completed | April 4, 2026, 11:19 a.m. |
Created at: March 30, 2026, 7:39 p.m.