Triple
T20697064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Len Wein |
E508685
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wein |
—
|
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: Wein | Statement: [Len Wein, familyName, Wein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wein Context triple: [Len Wein, familyName, Wein]
-
A.
Wein
chosen
Wein is a surname most notably associated with George Wein, the influential American jazz promoter and founder of major music festivals such as the Newport Jazz Festival.
-
B.
Winer
Winer is a surname most notably associated with Dave Winer, an influential software developer and pioneer of blogging and RSS technologies.
-
C.
Vino
Vino is a VNC-compatible remote desktop server for the GNOME desktop environment on Unix-like systems.
-
D.
Weinke
Weinke is a surname most notably associated with Chris Weinke, a former American football quarterback and Heisman Trophy winner.
-
E.
Winenne
Winenne is a small village in the municipality of Houyet in the Wallonia region of southern Belgium.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c1123d7c81908a1d16923437266d |
completed | April 21, 2026, 12:13 a.m. |
Created at: April 16, 2026, 12:10 p.m.