Triple
T14778112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Most Girls |
E347315
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Savan Kotecha |
E653108
|
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: Savan Kotecha | Statement: [Most Girls, writer, Savan Kotecha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Savan Kotecha Context triple: [Most Girls, writer, Savan Kotecha]
-
A.
Savan Kotecha
chosen
Savan Kotecha is an American songwriter and record producer best known for crafting numerous global pop hits for artists like One Direction, Ariana Grande, and The Weeknd.
-
B.
Divyank Turakhia
Divyank Turakhia is an Indian serial tech entrepreneur and billionaire best known for building and selling multiple internet and ad-tech companies, including those under the Directi Group.
-
C.
Karan Patel
Karan Patel is an Indian television actor best known for his role as Raman Bhalla in the popular Hindi TV series "Yeh Hai Mohabbatein."
-
D.
Dillon Mitra
Dillon Mitra is an actor known for his role in the culinary drama film "The Hundred-Foot Journey."
-
E.
Anish Savjani
Anish Savjani is an American film producer known for his work on acclaimed independent films, including the thriller "Green Room."
- 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_69d822e9b9e08190bedcc31a163fda82 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec817c39081909b08a0ffdfce9936 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24b626c48190a6aa9eda43539246 |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:31 a.m.