Triple
T24851992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grusha Vashnadze |
E621912
|
entity |
| Predicate | relationshipTo Michael Abashwili |
P93770
|
FINISHED |
| Object | foster 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: foster mother | Statement: [Grusha Vashnadze, relationshipTo Michael Abashwili, foster mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTo Michael Abashwili Context triple: [Grusha Vashnadze, relationshipTo Michael Abashwili, foster mother]
-
A.
relationshipTypeWithMikaelBoghosian
Indicates the specific nature or category of relationship that an entity has with Mikael Boghosian.
-
B.
relationshipTypeWithAlexeiIvanovich
Indicates the specific nature or category of relationship that an entity has with Alexei Ivanovich.
-
C.
relationshipStatusWithMichael
chosen
Indicates the type or state of the relationship that an entity currently has with Michael.
-
D.
relationshipToPolinaAlexandrovna
Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
-
E.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
- 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_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 18, 2026, 5:20 a.m.