Triple
T3496812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Brett Weiss |
E73870
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Weiss |
E68163
|
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: Weiss | Statement: [Daniel Brett Weiss, familyName, Weiss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weiss Context triple: [Daniel Brett Weiss, familyName, Weiss]
-
A.
Weiss
chosen
Weiss is a common German-language surname borne by numerous notable individuals across fields such as entertainment, science, and politics.
-
B.
Weiss/Manfredi
Weiss/Manfredi is a New York–based architecture and design firm known for its innovative, landscape-integrated cultural and institutional projects.
-
C.
Weis
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.
-
D.
Fall Weiss
Fall Weiss was the codename for Nazi Germany’s military plan to invade Poland in September 1939, marking the beginning of World War II in Europe.
-
E.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd16c0081908f13535f459618d1 |
completed | March 8, 2026, 6:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373cce4008190beb010b171bc4940 |
completed | March 13, 2026, 2:17 a.m. |
Created at: March 8, 2026, 3:18 p.m.