Triple
T3338522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Gardner |
E70198
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Neuralink |
E3335
|
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: Neuralink | Statement: [Tim Gardner, employer, Neuralink]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neuralink Context triple: [Tim Gardner, employer, Neuralink]
-
A.
Neuralink
chosen
Neuralink is a neurotechnology company developing implantable brain–computer interfaces aimed at enabling direct communication between the human brain and computers.
-
B.
positronic brain
A positronic brain is a fictional, highly advanced artificial intelligence device conceived by Isaac Asimov to serve as the thinking mechanism of robots in his Robot series.
-
C.
Kurzweil Applied Intelligence
Kurzweil Applied Intelligence is a technology company known for pioneering speech recognition and artificial intelligence software applications.
-
D.
Cyborg
Cyborg is a prominent DC Comics superhero, best known as a technologically enhanced human and key member of teams like the Teen Titans and the Justice League.
-
E.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1bd6c7c8190b7229de1433d8d20 |
completed | March 8, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b325191a38819095cdccca8f013774 |
completed | March 12, 2026, 8:42 p.m. |
Created at: March 8, 2026, 3:12 p.m.