Triple
T8693218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonny Lee Miller |
E206340
|
entity |
| Predicate | relativeTypeOfBernardLee |
P84223
|
FINISHED |
| Object | grandfather |
—
|
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: grandfather | Statement: [Jonny Lee Miller, relativeTypeOfBernardLee, grandfather]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeTypeOfBernardLee Context triple: [Jonny Lee Miller, relativeTypeOfBernardLee, grandfather]
-
A.
relativeTypeToNapoleonBonaparte
Indicates the specific familial relationship that an entity has to Napoleon Bonaparte.
-
B.
relationshipToLeeGates
Indicates the specific type of personal or professional relationship an entity has with Lee Gates.
-
C.
Lincoln Lewis
Indicates a relationship or association involving the entity or name "Lincoln Lewis," such as authorship, participation, or attribution in a given context.
-
D.
relativeTypeOfFannyVonWilamowitzMoellendorff
Indicates that one entity is a relative (by family relationship) of Fanny von Wilamowitz-Moellendorff.
-
E.
relationshipToBillyBackus
Indicates the specific familial or social relationship that an entity has to the person named Billy Backus.
- F. None of above. chosen
Provenance (4 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5826bbb48190a212fb1bb06e05e6 |
completed | March 31, 2026, 11:26 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc483f06f48190879f4702c8b4ed00 |
completed | March 31, 2026, 10:18 p.m. |
Created at: March 30, 2026, 6:33 p.m.