Triple
T22710680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Strauss |
E561585
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Arthur Strauss |
—
|
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: Arthur Strauss | Statement: [George Strauss, child, Arthur Strauss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arthur Strauss Context triple: [George Strauss, child, Arthur Strauss]
-
A.
Arthur Strauss
chosen
Arthur Strauss is the son of British Labour politician George Strauss.
-
B.
Morris Langer
Morris Langer was an American mathematician known for his contributions to functional analysis and differential equations.
-
C.
Paul Klemperer
Paul Klemperer is a British economist renowned for his work on auction theory and market design, including contributions that shaped major spectrum auctions.
-
D.
J. G. N. Strauss
J. G. N. Strauss was a South African politician who led the United Party during the apartheid era and served as Leader of the Opposition in Parliament.
-
E.
Leon Isserlis
Leon Isserlis was a British statistician best known for Isserlis’ theorem, which provides formulas for higher-order moments of multivariate normal distributions.
- 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17907d7288190bb53f76974f95cef |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:17 p.m.