Triple
T4746675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Luan |
E105375
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Adept AI |
E466275
|
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: Adept AI | Statement: [David Luan, employer, Adept AI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adept AI Context triple: [David Luan, employer, Adept AI]
-
A.
Adept AI
chosen
Adept AI is an artificial intelligence research and product company focused on building AI agents that can use existing software tools to perform complex tasks for users.
-
B.
Kurzweil Applied Intelligence
Kurzweil Applied Intelligence is a technology company known for pioneering speech recognition and artificial intelligence software applications.
-
C.
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.
-
D.
Robust.AI
Robust.AI is a robotics company focused on building practical, intelligent robot systems for real-world environments, co-founded by renowned roboticist Rodney Brooks.
-
E.
AI2
AI2 is a research institute founded by Paul Allen that advances artificial intelligence through open science, impactful AI systems, and large-scale scholarly resources.
- 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c3fcb081909b1fe867b4adac8b |
completed | March 20, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43b24440819081f3932eb6b68b48 |
completed | March 21, 2026, 7:07 a.m. |
Created at: March 20, 2026, 1:20 p.m.