Triple
T25178339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daru Shezad |
E630511
|
entity |
| Predicate | relationshipTypeWith Mumtaz |
P179444
|
FINISHED |
| Object | love affair |
—
|
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: love affair | Statement: [Daru Shezad, relationshipTypeWith Mumtaz, love affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Mumtaz Context triple: [Daru Shezad, relationshipTypeWith Mumtaz, love affair]
-
A.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
-
B.
associatedPersonRelationToMuhammad
Indicates the specific type of relationship or connection a person has to Muhammad.
-
C.
relationshipTypeWithSohni
Indicates the specific nature or category of the relationship an entity has with Sohni.
-
D.
marriageToDaraShikoh
Indicates a marital relationship in which the subject is married to Dara Shikoh.
-
E.
relationshipToAlauddinKhalji
Indicates the nature of a person or entity’s relationship or connection to Alauddin Khalji.
- 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_69e75a88fdf081908e47ae6e195c14e1 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f722c1bc648190a79bfdc722dcaaa4 |
completed | May 3, 2026, 10:26 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
| PDg | Predicate description generation | batch_69f7221bc57c819085c1464a45e61b2f |
completed | May 3, 2026, 10:23 a.m. |
Created at: April 21, 2026, 12:35 p.m.