Triple
T25654033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madhabi Mukherjee as Charulata |
E643179
|
entity |
| Predicate | characterHusband |
P138299
|
FINISHED |
| Object | Bhupati |
—
|
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: Bhupati | Statement: [Madhabi Mukherjee as Charulata, characterHusband, Bhupati]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterHusband Context triple: [Madhabi Mukherjee as Charulata, characterHusband, Bhupati]
-
A.
spouseCharacterOf
chosen
Indicates a marital relationship where one character is the spouse of another character.
-
B.
spouseCharacteristic
Indicates that a particular characteristic, trait, or attribute is associated with a person’s spouse within the relationship.
-
C.
spouseCharacterization
Indicates how one spouse describes, evaluates, or characterizes the other spouse within their relationship.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
spouseOfWork
Indicates that one person is the spouse of another specifically in the context of their workplace or professional environment.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 21, 2026, 6:31 p.m.