Triple
T10969692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terry Sanford |
E259199
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Sanford |
E670617
|
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: Sanford | Statement: [Terry Sanford, familyName, Sanford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sanford Context triple: [Terry Sanford, familyName, Sanford]
-
A.
Sanford
Sanford is the given first name of legendary American Major League Baseball pitcher Sandy Koufax.
-
B.
Sanford
Sanford is a major American manufacturer of writing instruments, best known as the parent company behind brands like Sharpie and Paper Mate.
-
C.
Sanford
Sanford is a small rural town located in Conejos County in southern Colorado, known for its agricultural surroundings and close-knit community.
-
D.
Sanford
Sanford is a city in central North Carolina that serves as a regional hub for education, industry, and commerce.
-
E.
Sanford
chosen
Sanford is a surname most notably associated with American actress Isabel Sanford, famed for her role as Louise "Weezy" Jefferson on the sitcom The Jeffersons.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77198e5408190904b2bb603d1bc16 |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d790df108190b4a3a6fece372778 |
completed | April 18, 2026, 1 a.m. |
Created at: April 8, 2026, 9:24 p.m.