Triple
T22833258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahiwal |
E565863
|
entity |
| Predicate | relationshipTypeWithSohni |
P149900
|
FINISHED |
| Object | forbidden love |
—
|
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: forbidden love | Statement: [Mahiwal, relationshipTypeWithSohni, forbidden love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithSohni Context triple: [Mahiwal, relationshipTypeWithSohni, forbidden love]
-
A.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
B.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
intraVedicRelation
Indicates a relationship that connects elements within the Vedic corpus itself, such as links between Vedic texts, concepts, or traditions.
-
D.
relationshipToSita
Indicates the specific familial, social, or interpersonal relationship that one entity has to Sita.
-
E.
relationToNurJahan
Indicates a relationship or connection that an entity has specifically to Nur Jahan.
- 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_69e24585ab1c81909b2b5065d15805d5 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e2d830881908d69929b854aad66 |
completed | April 29, 2026, 3:42 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:35 p.m.