Triple
T11221526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Keene |
E265578
|
entity |
| Predicate | loveInterestOf |
P7325
|
FINISHED |
| Object | Peter P. Peters |
E229583
|
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 P. Peters | Statement: [Linda Keene, loveInterestOf, Peter P. Peters]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter P. Peters Context triple: [Linda Keene, loveInterestOf, Peter P. Peters]
-
A.
Peter P. Peters
chosen
Peter P. Peters is the tap-dancing American ballet star played by Fred Astaire in the 1937 musical film "Shall We Dance."
-
B.
Peter J. Peters
Peter J. Peters is a researcher noted for his taxonomic and descriptive work on the Antarctic fur seal.
-
C.
Peter C. Frank
Peter C. Frank is an editor known for his work on the publication "The Verdict."
-
D.
H. Peter Hofstee
H. Peter Hofstee is a computer engineer and microprocessor architect best known for his work on advanced processor designs, including contributions at Transmeta and IBM.
-
E.
Peter E. Haas
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.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8ec8fb08190b27144ab65f85957 |
completed | April 9, 2026, 5:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef127eaf588190aaca151ee4022f3c |
completed | April 27, 2026, 7:38 a.m. |
Created at: April 8, 2026, 9:30 p.m.