Triple
T21662598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rinke Khanna |
E534628
|
entity |
| Predicate | relationToAkshayKumar |
P144904
|
FINISHED |
| Object | sister-in-law |
—
|
LITERAL 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: sister-in-law | Statement: [Rinke Khanna, relationToAkshayKumar, sister-in-law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToAkshayKumar Context triple: [Rinke Khanna, relationToAkshayKumar, sister-in-law]
-
A.
linkedToFilmStar
Indicates that one entity has a direct connection or association with a film star.
-
B.
relationshipWithBharata
Indicates that there exists a specific type of relationship or association between an entity and Bharata.
-
C.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
-
D.
relationshipToAmir
Indicates that one entity has a specified personal, social, or familial relationship to the person Amir.
-
E.
relationshipToRama
Indicates the specific familial, social, or other relational connection that an entity has to Rama.
- F. None of above. chosen
Provenance (4 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_69e0c467e1f48190af2650b19175abc4 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef6c0956e0819093b4794418efe052 |
completed | April 27, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69b4aa2b48190830107391e81571a |
completed | April 20, 2026, 9:31 p.m. |
Created at: April 16, 2026, 6:36 p.m.