Triple
T6817342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elsie Ann Ford |
E156799
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Pound |
E120693
|
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: Pound | Statement: [Elsie Ann Ford, notableWork, Pound]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pound Context triple: [Elsie Ann Ford, notableWork, Pound]
-
A.
Pound
chosen
Pound is a surname most famously associated with Ezra Pound, the influential American poet and critic central to the early modernist movement.
-
B.
Sterling
Sterling is a suburban community in Loudoun County, Northern Virginia, known for its residential neighborhoods, proximity to Washington Dulles International Airport, and role as part of the greater Washington, D.C. metropolitan area.
-
C.
Sterling
Sterling is a city in northern Illinois known as a regional industrial and commercial center along the Rock River.
-
D.
Sterling
Sterling is a masculine given name of English origin, often associated with qualities of high value or excellence.
-
E.
Doller
The Doller is a river in northeastern France that flows through the Alsace region and joins the Ill near Mulhouse.
- 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723e0c62c8190b3b3b092ea48d4c5 |
completed | March 28, 2026, 12:42 a.m. |
Created at: March 27, 2026, 2:17 p.m.