Triple
T6767219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimbal Musk |
E154752
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Musk |
E156625
|
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: Musk | Statement: [Kimbal Musk, familyName, Musk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Musk Context triple: [Kimbal Musk, familyName, Musk]
-
A.
Musk
chosen
Musk is a prominent surname most widely associated with entrepreneur Elon Musk and his family, including businessman and restaurateur Kimbal Musk.
-
B.
Elon Musk
Elon Musk is a billionaire entrepreneur and engineer best known for founding SpaceX, leading Tesla, and driving innovation in electric vehicles, space exploration, and other frontier technologies.
-
C.
Errol Musk
Errol Musk is a South African electromechanical engineer, pilot, and property developer best known as the controversial father of entrepreneur Elon Musk.
-
D.
Maye Musk
Maye Musk is a Canadian-South African model and dietitian who has had a decades-long international modeling career and is the mother of entrepreneur Elon Musk.
-
E.
Tosca Musk
Tosca Musk is a South African–Canadian filmmaker and producer, best known as the co-founder and CEO of the romance-focused streaming platform Passionflix.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2303c6881909405f0d6089dbe12 |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712c150088190b7e827cb1e45f1df |
completed | March 27, 2026, 11:29 p.m. |
Created at: March 27, 2026, 2:12 p.m.