Triple
T36588668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Butler Johnston |
E902601
|
entity |
| Predicate | hasTasteReflectedIn |
P152760
|
FINISHED |
| Object | Johnston–Felton–Hay House |
—
|
NE NERFINISHED |
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: Johnston–Felton–Hay House | Statement: [William Butler Johnston, hasTasteReflectedIn, Johnston–Felton–Hay House]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTasteReflectedIn Context triple: [William Butler Johnston, hasTasteReflectedIn, Johnston–Felton–Hay House]
-
A.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
B.
tasteInfluence
chosen
Indicates how one entity’s characteristics, actions, or presence affect or shape another entity’s preferences, likes, or aesthetic tastes.
-
C.
hasTastingProfile
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
-
D.
reflects
Indicates that one entity (often a surface, medium, or representation) throws back, mirrors, or otherwise shows an image, property, or state of another entity.
-
E.
tasteComparedTo
Indicates a comparison of the taste or flavor of one entity relative to another.
- 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_69f76e6592e88190bac4eb00a46e9df9 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:11 p.m.