Triple
T15062372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Hodak |
E379659
|
entity |
| Predicate | hasFormerPosition |
P107616
|
FINISHED |
| Object | former president of Neuralink |
—
|
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: former president of Neuralink | Statement: [Max Hodak, hasFormerPosition, former president of Neuralink]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerPosition Context triple: [Max Hodak, hasFormerPosition, former president of Neuralink]
-
A.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
B.
hasFormerStaffMember
Indicates that an entity once had a person as a staff member, but that person is no longer employed there.
-
C.
mayHavePriorRole
Indicates that an entity is allowed or expected to have held a specified role at some earlier time.
-
D.
officePreviouslyHeldBy
Indicates that a particular office or position was formerly occupied by a specified person or entity.
-
E.
hasFormerLeader
Indicates that an entity previously held the role of leader of another entity but no longer does.
- F. None of above.
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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee6a55c8190b40c4672fb46b79b |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.