Triple
T6652195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisner |
E150848
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Wiesner |
E71266
|
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: Wiesner | Statement: [Wisner, hasVariant, Wiesner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wiesner Context triple: [Wisner, hasVariant, Wiesner]
-
A.
Wiesner
chosen
Wiesner is a German-origin surname borne by various notable individuals across fields such as science, politics, and the arts.
-
B.
Shamir
Shamir is a Hebrew surname most prominently associated with Yitzhak Shamir, a former Prime Minister of Israel.
-
C.
Rabin
Rabin is a surname most prominently associated with Yitzhak Rabin, the Israeli military leader, statesman, and Nobel Peace Prize–winning prime minister.
-
D.
Ralph Merkle
Ralph Merkle is an American computer scientist and cryptographer known as a pioneer of public-key cryptography and for contributions such as Merkle trees and Merkle–Damgård hashing.
-
E.
Richard Mettler
Richard Mettler is a film editor known for his work on the 2016 war thriller "Anthropoid."
- 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b046c1408190af288575e40936d0 |
completed | March 27, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eefb3b6c8190ba797dc51966e3a5 |
completed | March 27, 2026, 8:56 p.m. |
Created at: March 27, 2026, 2:01 p.m.