Triple
T18724621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pranav Shyam |
E457864
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Pranav |
—
|
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 | Statement: [Pranav Shyam, hasGivenName, Pranav]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pranav Context triple: [Pranav Shyam, hasGivenName, Pranav]
-
A.
Pranav Murali
Pranav Murali is an academic or researcher known for co-authoring scholarly work with Pranav Shyam.
-
B.
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.
-
C.
Nishant
Nishant is a critically acclaimed 1975 Indian parallel cinema film directed by Shyam Benegal that explores themes of feudal oppression and social injustice in rural India.
-
D.
Pravin
Pravin is a common Indian given name, notably borne by South African politician and former finance minister Pravin Gordhan.
-
E.
Nikhil
Nikhil is an individual whose ideological views differ significantly from those held by Sandip.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d72d2c4819080b0d31860976b5e |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:50 a.m.