Triple
T22224101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jai Stephen Courtney |
E549289
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jai |
—
|
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: Jai | Statement: [Jai Stephen Courtney, givenName, Jai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jai Context triple: [Jai Stephen Courtney, givenName, Jai]
-
A.
Jai
chosen
Jai is the given name of Australian actor Jai Courtney, known for his roles in action and blockbuster films.
-
B.
Jai
Jai is an Indian actor best known for his work in Tamil cinema, particularly for his breakout performance in the critically acclaimed film "Subramaniapuram."
-
C.
Jai Pol
Jai Pol is a historic victory gate at Mehrangarh Fort in Jodhpur, India, built to commemorate a Rajput military triumph.
-
D.
Sanjay
Sanjay is the given name of Sanjay Gandhi, an influential and controversial Indian politician and son of former Prime Minister Indira Gandhi.
-
E.
Sanjay
Sanjay is the central protagonist of the 1965 film "Shakespeare-Wallah," around whom the story of a traveling Shakespearean theatre troupe in post-colonial India revolves.
- 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_69e11e403d6481909a94d0aaf157f6ef |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b92b79c8190a8a4d33591abd763 |
completed | April 28, 2026, 9:50 p.m. |
Created at: April 16, 2026, 8:37 p.m.