Triple
T21599442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexei Ivanovich |
E532994
|
entity |
| Predicate | relationshipToGeneral |
P10690
|
FINISHED |
| Object | employee |
—
|
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: employee | Statement: [Alexei Ivanovich, relationshipToGeneral, employee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToGeneral Context triple: [Alexei Ivanovich, relationshipToGeneral, employee]
-
A.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
B.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
-
E.
relationshipToParents
Indicates the type or nature of a person's familial relationship to their parents.
- 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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefae4746c819090afe1d93fe9f175 |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.