Triple
T1930592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willard F. Libby |
E40934
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Leona Woods |
E50935
|
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: Leona Woods | Statement: [Willard F. Libby, spouse, Leona Woods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leona Woods Context triple: [Willard F. Libby, spouse, Leona Woods]
-
A.
Leona Woods
chosen
Leona Woods was an American physicist who, as one of the few women on the Manhattan Project, played a key role in the development and operation of the first nuclear reactor.
-
B.
Jane Wilson
Jane Wilson was the wife of British Prime Minister Spencer Perceval and a member of the English gentry in the late 18th and early 19th centuries.
-
C.
Laura
Laura is a feminine given name of Latin origin, commonly used in many languages and cultures.
-
D.
Laura
Laura is a classic 1944 American film noir mystery celebrated for its sophisticated storytelling, atmospheric cinematography, and iconic score.
-
E.
Katrina Maley Wheeler
Katrina Maley Wheeler is the wife of Portland, Oregon politician and former mayor Ted Wheeler.
- 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_69a8864711648190b07bed24ed76258e |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb296910481908c9668518c09fdb0 |
completed | March 7, 2026, 5:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3ef29e0819081b37664224dee91 |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:35 p.m.