Triple
T13675782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arcadia |
E327872
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Hannah Jarvis |
E873516
|
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: Hannah Jarvis | Statement: [Arcadia, hasCharacter, Hannah Jarvis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannah Jarvis Context triple: [Arcadia, hasCharacter, Hannah Jarvis]
-
A.
Hannah Jarvis
chosen
Hannah Jarvis is a sharp-tongued, intellectually driven author and researcher in Tom Stoppard’s play "Arcadia," investigating the history of the Sidley Park estate.
-
B.
Hannah Lorimer
Hannah Lorimer is the mother of Robert Lorimer, a notable Scottish architect of the late 19th and early 20th centuries.
-
C.
Hannah Gale
Hannah Gale is known primarily as the wife of English actor John Glover.
-
D.
Hannah Bagshawe
Hannah Bagshawe is a British public relations executive known for her work in the financial sector and for being married to actor Eddie Redmayne.
-
E.
Julia Biggs
Julia Biggs is the warm, devoted church wife and mother at the heart of the film "The Preacher's Wife," portrayed by Whitney Houston.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65c04988190b675e6fb7241e53c |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7943dbf748190b41abfe9d81d1427 |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:53 p.m.