Triple
T20451192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marvell Technology, Inc. |
E501652
|
entity |
| Predicate | Matt Murphy role |
P140151
|
FINISHED |
| Object | President and Chief Executive Officer |
—
|
LITERAL 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: President and Chief Executive Officer | Statement: [Marvell Technology, Inc., Matt Murphy role, President and Chief Executive Officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Matt Murphy role Context triple: [Marvell Technology, Inc., Matt Murphy role, President and Chief Executive Officer]
-
A.
RobMorrowRole
Indicates that a person has played a specific role in a work featuring Rob Morrow.
-
B.
roleOfBobbyMurphy
Indicates the specific role, position, or function that Bobby Murphy holds in relation to another entity or context.
-
C.
Russell Thompkins Jr. role
Indicates that Russell Thompkins Jr. holds or held a particular role, position, or function in relation to another entity or context.
-
D.
Dwight MerrimanRole
Indicates that Dwight Merriman holds or has held a specific role or position in relation to another entity.
-
E.
Matthew DayeRole
Indicates that Matthew has or performs a specific role, function, or position in relation to another entity.
- F. None of above. chosen
Provenance (4 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68d0296ac819081e74c67d3cc6349 |
completed | April 20, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:32 a.m.