Triple
T9619588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velutha |
E232306
|
entity |
| Predicate | relationshipTypeWithAmmu |
P10690
|
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: [Velutha, relationshipTypeWithAmmu, Forbidden love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithAmmu Context triple: [Velutha, relationshipTypeWithAmmu, Forbidden love]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
relationshipEnd
Indicates that a previously existing relationship between entities has been terminated or has come to an end.
-
E.
identityRelation
Indicates that two entities are in fact the very same entity, not merely similar or equivalent.
- F. None of above.
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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad295008190a4418d092576cb53 |
completed | April 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69ccd5aa1d2c8190a287bf1cf4a3037e |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:09 p.m.