Triple
T2044261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Wainwright (DD-419) |
E45413
|
entity |
| Predicate | class |
P87
|
FINISHED |
| Object | Sims class |
E6217
|
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: Sims class | Statement: [USS Wainwright (DD-419), class, Sims class]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sims class Context triple: [USS Wainwright (DD-419), class, Sims class]
-
A.
Sims class
chosen
The Sims class was a group of United States Navy destroyers built just before World War II that served extensively in the Atlantic and Pacific theaters.
-
B.
Sis
Sis was the medieval capital city of the Armenian Kingdom of Cilicia, serving as its political and cultural center.
-
C.
SIS
SIS is the commonly used abbreviation for the United Kingdom’s Secret Intelligence Service, the foreign intelligence agency often referred to as MI6.
-
D.
Simulator
Simulator is Apple's iOS and watchOS device emulation tool bundled with Xcode, used by developers to run and test apps on virtual Apple devices.
-
E.
Odyssey Sims
Odyssey Sims is an American professional basketball guard known for her standout collegiate career at Baylor University and subsequent success in the WNBA.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb97153b08190b91d82f4117982be |
completed | March 7, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae271399a08190946b315f439b9b2f |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:39 p.m.