Triple
T10549583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter A. Haas Jr. |
E248911
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Peter E. Haas |
E354630
|
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: Peter E. Haas | Statement: [Walter A. Haas Jr., relative, Peter E. Haas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter E. Haas Context triple: [Walter A. Haas Jr., relative, Peter E. Haas]
-
A.
Peter E. Haas
chosen
Peter E. Haas was an American businessman and philanthropist best known for his leadership role at Levi Strauss & Co. and his prominent involvement in civic and charitable causes in San Francisco.
-
B.
Richard Haas
Richard Haas is an American painter and muralist renowned for his large-scale architectural trompe-l'œil works that transform urban building facades.
-
C.
Peter A. Ziegler
Peter A. Ziegler was a prominent Swiss geologist known for his influential work on the tectonic evolution and geological history of Europe.
-
D.
Thomas F. Hofmann
Thomas F. Hofmann is a German food chemist and academic leader who serves as president of the Technical University of Munich.
-
E.
Peter J. Weinberger
Peter J. Weinberger is an American computer scientist known for his contributions to programming languages and tools at Bell Labs, including co-creating the AWK programming language.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d526d3e45c819099b360f9cfd3dd50 |
completed | April 7, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e877c6188190817fb30f2c9a07bf |
completed | April 20, 2026, 8:48 a.m. |
Created at: April 6, 2026, 12:33 p.m.