Triple
T8031096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariana |
E186978
|
entity |
| Predicate | inspiredByAuthor |
P61130
|
FINISHED |
| Object | Alfred Tennyson |
E58639
|
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: Alfred Tennyson | Statement: [Mariana, inspiredByAuthor, Alfred Tennyson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alfred Tennyson Context triple: [Mariana, inspiredByAuthor, Alfred Tennyson]
-
A.
Alfred, Lord Tennyson
chosen
Alfred, Lord Tennyson was a prominent 19th-century British poet who served as Poet Laureate and became one of the most celebrated voices of the Victorian age.
-
B.
Lionel Tennyson
Lionel Tennyson was one of the sons of Victorian poet Alfred, Lord Tennyson, known primarily through his connection to his father's life and legacy.
-
C.
Frederick Tennyson
Frederick Tennyson was a 19th-century English poet and the elder brother of Alfred, Lord Tennyson.
-
D.
George Clayton Tennyson
George Clayton Tennyson was an English clergyman and lawyer best known as the father of the poet Alfred, Lord Tennyson.
-
E.
Matthew Arnold
Matthew Arnold was a 19th-century English poet and cultural critic known for works like "Dover Beach" and for his influential essays on literature, education, and society.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3eef921081908d0ea21f142c175a |
completed | March 31, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56e812dc81908916fc7163ae344a |
completed | March 31, 2026, 11:21 p.m. |
Created at: March 30, 2026, 5:22 p.m.