Triple
T24772967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bill Tanner |
E619778
|
entity |
| Predicate | relationshipToM |
P10690
|
FINISHED |
| Object | trusted aide |
—
|
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: trusted aide | Statement: [Bill Tanner, relationshipToM, trusted aide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToM Context triple: [Bill Tanner, relationshipToM, trusted aide]
-
A.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
relationshipToUser
Indicates the type of connection or association an entity has with the current user.
-
D.
addressesRelationship
Indicates that one entity directs communication, remarks, or attention specifically toward another entity.
-
E.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 18, 2026, 4:32 a.m.