Triple
T18823674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Pepper |
E460328
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Pepper |
—
|
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: Pepper | Statement: [William Pepper, hasSurname, Pepper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pepper Context triple: [William Pepper, hasSurname, Pepper]
-
A.
Pepper
chosen
Pepper is a common English surname borne by various notable individuals across fields such as medicine, politics, and the arts.
-
B.
Pepper
Pepper is a tough, streetwise orphan girl from the musical "Annie," known for her brash attitude and leadership among the other children in Miss Hannigan’s orphanage.
-
C.
Pepper
Pepper is a character romantically involved with Harry Bright in the story’s narrative.
-
D.
Pepper
Pepper is a supporting character in the 2003 horror film "The Texas Chainsaw Massacre," known for being one of the ill-fated young travelers who encounter Leatherface and his murderous family.
-
E.
Pepperjack
Pepperjack is an Australian wine brand best known for its bold, full-bodied red wines, particularly Shiraz, often crafted to pair well with grilled meats.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bce5588190bd0aefcd0c51edad |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 10, 2026, 11:56 a.m.