Triple
T11694994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanjay Kapoor |
E277970
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Prem |
E785192
|
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: Prem | Statement: [Sanjay Kapoor, notableWork, Prem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prem Context triple: [Sanjay Kapoor, notableWork, Prem]
-
A.
Prem
Prem is an Indian given name commonly used for males, derived from Sanskrit and meaning "love" or "affection."
-
B.
Prem
chosen
Prem is a small rural municipality in the district of Weilheim-Schongau in Bavaria, Germany.
-
C.
Pres
Pres was the nickname of Lester Young, the influential American jazz tenor saxophonist known for his cool tone and innovative, lyrical improvisational style.
-
D.
Per
Per is a Scandinavian masculine given name, commonly used in Norway, Sweden, and Denmark as a form of Peter.
-
E.
PRO
PRO is the Professional Referee Organization that manages and develops professional soccer match officials in the United States and Canada.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47b9eb48190976a35e91e25b56b |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.