Triple
T25694769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ketaki |
E644289
|
entity |
| Predicate | relationshipTypeWithAmit |
P10690
|
FINISHED |
| Object | complex romantic relationship |
—
|
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: complex romantic relationship | Statement: [Ketaki, relationshipTypeWithAmit, complex romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithAmit Context triple: [Ketaki, relationshipTypeWithAmit, complex romantic relationship]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipToAmir
Indicates that one entity has a specified personal, social, or familial relationship to the person Amir.
-
C.
relationshipToSita
Indicates the specific familial, social, or interpersonal relationship that one entity has to Sita.
-
D.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
E.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
- 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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd231cab588190ad0953dc8f4af8f2 |
completed | May 7, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69fd1aa3f1c481909fe6e9cab1383551 |
completed | May 7, 2026, 11:05 p.m. |
Created at: April 21, 2026, 8:33 p.m.