Triple
T15770335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Witherspoon |
E382335
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Witherspoon |
E78770
|
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: Witherspoon | Statement: [John Witherspoon, familyName, Witherspoon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Witherspoon Context triple: [John Witherspoon, familyName, Witherspoon]
-
A.
Witherspoon
chosen
Witherspoon is a Scottish-origin surname borne by various notable figures in politics, entertainment, and sports.
-
B.
Sophia Witherspoon
Sophia Witherspoon is a former American professional basketball guard best known for her WNBA career in the late 1990s and early 2000s.
-
C.
Elizabeth Sanders
Elizabeth Sanders is known as the wife of Batman co-creator Bob Kane and has occasionally been involved in preserving and promoting his legacy.
-
D.
Elizabeth Sanders
Elizabeth Sanders is best known as the wife of British historian and politician Conrad Russell, 5th Earl Russell.
-
E.
Angelina
Angelina is the kind-hearted heroine and title character of Rossini’s opera "La Cenerentola," a Cinderella-like figure who rises from servitude to happiness through virtue and forgiveness.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e051962fe08190a6201dd48196a9ee |
completed | April 16, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff877c5ae88190aeb500bb5f0d73f7 |
completed | May 9, 2026, 7:14 p.m. |
Created at: April 10, 2026, 4:47 a.m.