Triple
T22647486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Poets circle |
E559002
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Sara Hutchinson |
—
|
NE NERFINISHED |
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: Sara Hutchinson | Statement: [Lake Poets circle, hasMember, Sara Hutchinson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sara Hutchinson Context triple: [Lake Poets circle, hasMember, Sara Hutchinson]
-
A.
Sara Hutchinson
chosen
Sara Hutchinson was an English woman closely associated with the Romantic poet Samuel Taylor Coleridge, often remembered as his muse and confidante.
-
B.
Larissa Howard
Larissa Howard is known as the daughter of British military historian and politician Michael Howard.
-
C.
Catherine Hart
Catherine Hart is the daughter of American actress, singer, and television personality Kitty Carlisle.
-
D.
Kate Houghton
Kate Houghton is a central protagonist in the live-action/animated comedy film "Looney Tunes: Back in Action," where she works closely with classic Looney Tunes characters in a high-stakes adventure.
-
E.
Lisa Roughead
Lisa Roughead is the wife of former Manchester United and England footballer Michael Carrick and is known for largely maintaining a private life outside the public spotlight.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17039c2bc8190972a7c169b27005c |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:05 p.m.