Triple
T14129816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald Saddler |
E340131
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Saddler |
E437509
|
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: Saddler | Statement: [Donald Saddler, familyName, Saddler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saddler Context triple: [Donald Saddler, familyName, Saddler]
-
A.
Saddler
chosen
Saddler is a surname and occupational term historically referring to someone who makes, repairs, or sells saddles and other horse-related leather equipment.
-
B.
Shriever
Shriever is a surname, a variant spelling of "Shriver," borne by various individuals of English-speaking origin.
-
C.
Snodgrass
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
D.
Hunte
The Hunte is a river in northwestern Germany that flows through Lower Saxony before joining the Weser.
-
E.
Laddie
Laddie is a film featuring American child actress Virginia Weidler in a prominent role.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de610aa434819096671c5aabb9134a |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdf0ed0a88190a7126887364fccdd |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 10:23 p.m.