Triple
T25694479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarbajaya Ray |
E644281
|
entity |
| Predicate | hasMaritalRelationshipWith |
P64467
|
FINISHED |
| Object | Harihar Ray |
—
|
NE NERFINISHED |
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: Harihar Ray | Statement: [Sarbajaya Ray, hasMaritalRelationshipWith, Harihar Ray]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalRelationshipWith Context triple: [Sarbajaya Ray, hasMaritalRelationshipWith, Harihar Ray]
-
A.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
B.
maritalRelations
chosen
Indicates a legally or socially recognized spousal relationship or marriage-based connection between two entities.
-
C.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
- 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_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 21, 2026, 8:33 p.m.