Triple
T21110284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amrish Puri |
E520153
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Amrish |
—
|
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: Amrish | Statement: [Amrish Puri, givenName, Amrish]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amrish Context triple: [Amrish Puri, givenName, Amrish]
-
A.
Amrish Puri
chosen
Amrish Puri was a renowned Indian actor best known for his powerful villainous roles in Hindi cinema and for playing the iconic antagonist Mola Ram in the film "Indiana Jones and the Temple of Doom."
-
B.
Ashvajit
Ashvajit is a Buddhist figure traditionally regarded as one of the early disciples present at the Buddha’s first sermon, the Turning of the Wheel of Dharma.
-
C.
HAL Ajeet
HAL Ajeet is an Indian light fighter aircraft developed by Hindustan Aeronautics Limited as an improved, license-built variant of the British Folland Gnat.
-
D.
Badal
Badal is a Barcelona Metro station that serves the area near Camp Nou stadium in Barcelona, Spain.
-
E.
Shyam
Shyam is the young protagonist of the classic Marathi autobiographical novel "Shyamchi Aai," depicting his deep bond with his mother and his moral and emotional growth.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72101f7308190beb202a052ff04d2 |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.