Triple
T9392353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guy Madison |
E226054
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Moseley |
E249169
|
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: Moseley | Statement: [Guy Madison, familyName, Moseley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moseley Context triple: [Guy Madison, familyName, Moseley]
-
A.
Moseley
chosen
Moseley is a surname most notably associated with Jonny Moseley, the American Olympic gold medal–winning freestyle skier.
-
B.
Wollaston
Wollaston is an English surname most notably associated with William Hyde Wollaston, the chemist and physicist who discovered the elements palladium and rhodium.
-
C.
Wollaston
Wollaston is a Massachusetts Bay Transportation Authority (MBTA) rapid transit station on the Red Line located in Quincy, Massachusetts.
-
D.
Rutherford
Rutherford is the given name of Rutherford B. Hayes, the 19th president of the United States.
-
E.
Rutherford
Rutherford is a renowned wine-growing region in Napa Valley, California, celebrated for its high-quality Cabernet Sauvignon and distinctive "Rutherford dust" terroir.
- 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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd510eae0c8190b7c4ab487a366bb3 |
completed | April 1, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1010169d88190a7267615a9196d4b |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:45 p.m.