Triple
T10353946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamal Malik |
E243949
|
entity |
| Predicate | loveInterest |
P7325
|
FINISHED |
| Object | Latika |
E248235
|
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: Latika | Statement: [Jamal Malik, loveInterest, Latika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Latika Context triple: [Jamal Malik, loveInterest, Latika]
-
A.
Latika
chosen
Latika is a central character in the film "Slumdog Millionaire," portrayed as the protagonist's childhood friend and love interest whose life intertwines with his journey from the Mumbai slums to game-show fame.
-
B.
Lasya
Lasya is a graceful, expressive classical Indian dance style traditionally associated with feminine beauty and gentle, fluid movements.
-
C.
Alinda
Alinda was an important ancient city in the region of Caria in southwestern Anatolia, known for its strategic location and well-preserved Hellenistic ruins.
-
D.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
E.
Katisha
Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e952c878819084e5d7a593a3f9e9 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d750a30af88190b2ebf0daf758ed44 |
completed | April 9, 2026, 7:09 a.m. |
Created at: April 6, 2026, 11:58 a.m.