Triple
T20552208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judith Faulkner |
E504622
|
entity |
| Predicate | sharesTrait |
P5696
|
FINISHED |
| Object | self-made billionaire |
—
|
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: self-made billionaire | Statement: [Judith Faulkner, sharesTrait, self-made billionaire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesTrait Context triple: [Judith Faulkner, sharesTrait, self-made billionaire]
-
A.
sharesFeatureWith
chosen
Indicates that two entities have at least one common attribute, property, or characteristic in common.
-
B.
sharesCharacterWith
Indicates that two entities have at least one character (such as a letter, symbol, or glyph) in common.
-
C.
sharesWith
Indicates that one entity gives another entity access to or use of something it possesses.
-
D.
sharesBaseWith
Indicates that two entities have a common underlying base element, source, or component from which they are derived or constructed.
-
E.
sharesAppearanceTraitWith
Indicates that two entities possess at least one similar or matching visual or appearance-related characteristic.
- 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_69e0b4b52c048190952b4d0f430813a3 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5d98c348190ac516bc2df59d878 |
completed | April 20, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:38 a.m.