Triple
T405882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maye Musk |
E9381
|
entity |
| Predicate | hasSibling |
P363
|
FINISHED |
| Object |
Kaye Haldeman
Kaye Haldeman is a member of the Musk family and the sister of model and dietitian Maye Musk.
|
E53849
|
NE FINISHED |
How this triple was built (4 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: Kaye Haldeman | Statement: [Maye Musk, hasSibling, Kaye Haldeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaye Haldeman Context triple: [Maye Musk, hasSibling, Kaye Haldeman]
-
A.
Maye Haldeman
Maye Haldeman is a Canadian-South African model and dietitian best known as Maye Musk, the mother of entrepreneur Elon Musk and a prominent figure in fashion and nutrition.
-
B.
Karen Verne
Karen Verne was a German-born actress who appeared in Hollywood films of the 1940s and was once married to actor Peter Lorre.
-
C.
Judith Nelson
Judith Nelson was an American soprano known for her pioneering work and acclaimed performances in the early music and Baroque repertoire.
-
D.
Janet Asimov
Janet Asimov was an American psychiatrist, psychoanalyst, and science fiction writer who collaborated with and was married to author Isaac Asimov.
-
E.
C. E. Webber
C. E. Webber was a British television writer and script editor credited with helping develop the original concept and format of the long-running science fiction series Doctor Who.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kaye Haldeman Triple: [Maye Musk, hasSibling, Kaye Haldeman]
Generated description
Kaye Haldeman is a member of the Musk family and the sister of model and dietitian Maye Musk.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaye Haldeman Target entity description: Kaye Haldeman is a member of the Musk family and the sister of model and dietitian Maye Musk.
-
A.
Maye Haldeman
chosen
Maye Haldeman is a Canadian-South African model and dietitian best known as Maye Musk, the mother of entrepreneur Elon Musk and a prominent figure in fashion and nutrition.
-
B.
Karen Verne
Karen Verne was a German-born actress who appeared in Hollywood films of the 1940s and was once married to actor Peter Lorre.
-
C.
Judith Nelson
Judith Nelson was an American soprano known for her pioneering work and acclaimed performances in the early music and Baroque repertoire.
-
D.
Janet Asimov
Janet Asimov was an American psychiatrist, psychoanalyst, and science fiction writer who collaborated with and was married to author Isaac Asimov.
-
E.
C. E. Webber
C. E. Webber was a British television writer and script editor credited with helping develop the original concept and format of the long-running science fiction series Doctor Who.
- F. None of above.
Provenance (5 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_69a2e8004cb88190b92ed1add6abf41a |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecbc00508190bbb602179273f29c |
completed | Feb. 28, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a431dd98dc8190a0020cdbeec5cfbf |
completed | March 1, 2026, 12:32 p.m. |
| NEDg | Description generation | batch_69a43267c1d081908b2036402ce0ec11 |
completed | March 1, 2026, 12:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a432f94a948190a958bba70c2fc806 |
completed | March 1, 2026, 12:37 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.