Triple
T14096285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel bat Kalba Savua |
E339260
|
entity |
| Predicate | vowRelatedTo |
P89916
|
FINISHED |
| Object | Kalba Savua’s vow to disinherit her |
—
|
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: Kalba Savua’s vow to disinherit her | Statement: [Rachel bat Kalba Savua, vowRelatedTo, Kalba Savua’s vow to disinherit her]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vowRelatedTo Context triple: [Rachel bat Kalba Savua, vowRelatedTo, Kalba Savua’s vow to disinherit her]
-
A.
associatedVow
chosen
Indicates a relationship where a vow is linked or connected to a particular entity or event.
-
B.
vowResult
Indicates that a vow or solemn promise leads to, results in, or is fulfilled by a particular outcome or state.
-
C.
vowStatus
Indicates the current state or condition of a commitment or promise made between entities, such as whether it is active, fulfilled, or broken.
-
D.
causeOfVow
Indicates that one event, condition, or entity is the reason or motivating factor behind another entity making a vow.
-
E.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fb7fb3c819083266dbe7e93aaff |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.