Triple
T333069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Nance Garner |
E6665
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Nance |
E9716
|
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: Nance | Statement: [John Nance Garner, middleName, Nance]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nance Context triple: [John Nance Garner, middleName, Nance]
-
A.
Nance
chosen
Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
B.
Nancy
Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
-
C.
Leslie
Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
-
D.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
E.
Maxine
Maxine is a character featured in the film "Once Again."
- 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_69a2e79434908190a9d5afe415153ad9 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eac4d9d081908a624464e450fb0e |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a436664f748190b8f360b1dfc0ff3d |
completed | March 1, 2026, 12:51 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.