Triple
T12581054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Elizabeth Cavendish |
E300335
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cavendish |
E48548
|
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: Cavendish | Statement: [Lady Elizabeth Cavendish, familyName, Cavendish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cavendish Context triple: [Lady Elizabeth Cavendish, familyName, Cavendish]
-
A.
Cavendish
chosen
Cavendish is a prominent English aristocratic family historically influential in politics, science, and society, associated with figures such as scientists Henry and William Cavendish and the Dukes of Devonshire.
-
B.
Cavendish
Cavendish is a picturesque village and civil parish in Suffolk, England, noted for its historic thatched cottages and traditional English countryside charm.
-
C.
Cavendish
Cavendish is the married surname of Kathleen Kennedy, a member of the prominent Kennedy family who became Marchioness of Hartington.
-
D.
Yates
Yates is a surname of English origin borne by various notable individuals across literature, politics, sports, and other fields.
-
E.
Daubeny
Daubeny is an English surname derived from the Norman French family name d’Aubigny.
- 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_69d7bde87b648190bcd0266e9efde098 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954b97a508190b6c901c506441dd0 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6559ba5108190b85be540a405eec8 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 9, 2026, 5:02 p.m.