Triple
T21108453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punnun |
E520112
|
entity |
| Predicate | relationshipTypeWithSassi |
P142888
|
FINISHED |
| Object | lover |
—
|
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: lover | Statement: [Punnun, relationshipTypeWithSassi, lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithSassi Context triple: [Punnun, relationshipTypeWithSassi, lover]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
relationshipToSita
Indicates the specific familial, social, or interpersonal relationship that one entity has to Sita.
-
E.
unitRelation
Indicates a relationship between units, such as how one unit is associated with, derived from, or converted to another.
- 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e720ffa998819082db225363ac3b23 |
completed | April 21, 2026, 7:02 a.m. |
| PD | Predicate disambiguation | batch_69e5dbff56848190a03b350a9305c612 |
completed | April 20, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69e5e2e03d88819086f8b641656ad8b0 |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 16, 2026, 2:54 p.m.