Triple
T21548695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Jones Lowndes |
E531700
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lowndes |
—
|
NE NERFINISHED |
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: Lowndes | Statement: [William Jones Lowndes, familyName, Lowndes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lowndes Context triple: [William Jones Lowndes, familyName, Lowndes]
-
A.
Lowndes
chosen
Lowndes is a surname most prominently associated with Australian racing driver Craig Lowndes.
-
B.
Lowndes County
Lowndes County is a rural county in central Alabama known for its significant role in the American civil rights movement, particularly during the Selma to Montgomery marches.
-
C.
Troup
Troup is a surname of Scottish origin borne by various notable individuals, including politicians, artists, and public figures.
-
D.
Hale County
Hale County is a rural county in west-central Alabama known for its agricultural landscape, small towns, and role in the Black Belt region.
-
E.
Lamar County
Lamar County is a rural county in western Alabama known for its small communities and agricultural landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45f17148190949c330ab9c27706 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeb590bb0881908cd849096696db10 |
completed | April 27, 2026, 1:02 a.m. |
Created at: April 16, 2026, 6:28 p.m.