Triple
T9617791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slaughter |
E232260
|
entity |
| Predicate | hasSpellingVariant |
P457
|
FINISHED |
| Object | Slater |
E755214
|
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: Slater | Statement: [Slaughter, hasSpellingVariant, Slater]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slater Context triple: [Slaughter, hasSpellingVariant, Slater]
-
A.
Slater
chosen
Slater is a small city located in central Iowa, United States.
-
B.
Salter
Salter is the middle name of Lucile Salter Packard, the American philanthropist and namesake of the Lucile Packard Children's Hospital at Stanford.
-
C.
Sadler
Sadler is an English-language surname borne by various notable individuals across fields such as politics, sports, and the arts.
-
D.
Shuler
Shuler is a surname most notably associated with Heath Shuler, a former NFL quarterback and U.S. Congressman from North Carolina.
-
E.
Saddler
Saddler is a surname and occupational term historically referring to someone who makes, repairs, or sells saddles and other horse-related leather equipment.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9aaf3a088190a00a7750c25b6c42 |
completed | April 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d17965cce08190862ea8a48addf0a2 |
completed | April 4, 2026, 8:49 p.m. |
Created at: March 30, 2026, 8:09 p.m.