Triple
T16798720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lally Weymouth |
E408298
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Elizabeth |
E1128956
|
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: Elizabeth | Statement: [Lally Weymouth, givenName, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Lally Weymouth, givenName, Elizabeth]
-
A.
Elizabeth
Elizabeth is a central character in the 1931 horror film "Frankenstein," serving as Henry Frankenstein’s fiancée and a key figure whose vulnerability heightens the story’s emotional and dramatic stakes.
-
B.
Elizabeth
Elizabeth was the Duchess of York who later became Queen Elizabeth The Queen Mother, a prominent member of the British royal family in the 20th century.
-
C.
Elizabeth
Elizabeth is the given name of Elizabeth Jane Cochrane, better known as pioneering American investigative journalist Nellie Bly.
-
D.
Elizabeth
Elizabeth of Denmark was a 16th-century Danish princess who became Electress of Brandenburg through her marriage to Joachim II Hector.
-
E.
Elizabeth
chosen
Elizabeth is the given first name of American actress Bess Armstrong, known for her work in film and television since the late 1970s.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2abc430819080c1303eded5f416 |
completed | April 18, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab1299ac81908e9f1eebc3424bb9 |
completed | May 10, 2026, 3:58 p.m. |
Created at: April 10, 2026, 5:22 a.m.