Triple
T10684425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Weis |
E251838
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Weis |
E251838
|
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: Weis | Statement: [Charlie Weis, familyName, Weis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weis Context triple: [Charlie Weis, familyName, Weis]
-
A.
Weis
chosen
Weis is a surname most prominently associated with Charlie Weis, an American football coach known for his tenure with the Notre Dame Fighting Irish and in the NFL.
-
B.
Bramble
Bramble is a modern classic gin-based cocktail typically made with lemon juice, sugar syrup, and blackberry liqueur, served over crushed ice.
-
C.
Steffl
Steffl is the popular nickname for the iconic south tower of St. Stephen's Cathedral in Vienna, a prominent symbol of the city's skyline.
-
D.
Wiebe
Wiebe is a given name and surname of Frisian and Dutch origin, used in various forms across the Netherlands and surrounding regions.
-
E.
Wuhl
Wuhl is the surname of American actor, comedian, and writer Robert Wuhl, known for his roles in films like "Bull Durham" and the TV series "Arliss."
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fcc5134c8190bcb1d96a32634c17 |
completed | April 9, 2026, 1:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9888cf7b481909de6a4fecb48cf4b |
completed | April 10, 2026, 11:32 p.m. |
Created at: April 8, 2026, 9:10 p.m.