Triple
T24852073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Natella Abashwili |
E621914
|
entity |
| Predicate | relationshipToMichael |
P93770
|
FINISHED |
| Object | mother |
—
|
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: mother | Statement: [Natella Abashwili, relationshipToMichael, mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMichael Context triple: [Natella Abashwili, relationshipToMichael, mother]
-
A.
relationshipToMike
Indicates the specific type of personal, social, or familial relationship that an entity has with Mike.
-
B.
relationshipStatusWithMichael
chosen
Indicates the type or state of the relationship that an entity currently has with Michael.
-
C.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
D.
relationshipToMary
Indicates that one entity stands in a specified personal or social relationship to Mary.
-
E.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
- 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_69e2fac297e481909d3aedc75f585e42 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 18, 2026, 5:20 a.m.