Triple
T19634087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom B. Brown |
E471343
|
entity |
| Predicate | coAuthorWith |
P398
|
FINISHED |
| Object | Pranav Shyam |
—
|
NE NERFINISHED |
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: Pranav Shyam | Statement: [Tom B. Brown, coAuthorWith, Pranav Shyam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pranav Shyam Context triple: [Tom B. Brown, coAuthorWith, Pranav Shyam]
-
A.
Pranav Shyam
chosen
Pranav Shyam is a computer scientist and AI researcher known for co-authoring influential work in large-scale language models alongside Tom B. Brown and others.
-
B.
Pranav Murali
Pranav Murali is an academic or researcher known for co-authoring scholarly work with Pranav Shyam.
-
C.
Shreyas Jain
Shreyas Jain is an Indian screenwriter best known for co-writing the critically acclaimed and commercially successful Bollywood film "Dangal."
-
D.
Varun Krishna
Varun Krishna is a business executive known for his leadership role at Rocket Companies, Inc., a major U.S.-based fintech and mortgage lending firm.
-
E.
Raghav Bhalla
Raghav Bhalla is an individual notable enough to be specifically cited as a bearer of the Bhalla surname.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64104ff2881908fec49b7fba5a2e6 |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.