Triple
T19565155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vaidehi |
E489562
|
entity |
| Predicate | maritalStatusInEpic |
P47938
|
FINISHED |
| Object | married to Rama |
—
|
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: married to Rama | Statement: [Vaidehi, maritalStatusInEpic, married to Rama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalStatusInEpic Context triple: [Vaidehi, maritalStatusInEpic, married to Rama]
-
A.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
-
B.
spouseStatus
Indicates the marital relationship status between two individuals, such as whether they are currently spouses, formerly spouses, or not married to each other.
-
C.
maritalStatusInMyth
chosen
Indicates the marital status or relationship state of an entity as portrayed within a specific myth or mythological tradition.
-
D.
hasCivilStatus
Indicates the civil or marital status that applies to a person or entity (e.g., single, married, divorced).
-
E.
hasMaritalRelationshipType
Indicates the specific type or nature of the marital relationship that exists between two entities.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f76b220819096e668534c6bac67 |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.