Triple
T31508488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapestry Chambers |
E803879
|
entity |
| Predicate | reflectsTasteOf |
P152760
|
FINISHED |
| Object | King Ludwig II of Bavaria |
—
|
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: King Ludwig II of Bavaria | Statement: [Tapestry Chambers, reflectsTasteOf, King Ludwig II of Bavaria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reflectsTasteOf Context triple: [Tapestry Chambers, reflectsTasteOf, King Ludwig II of Bavaria]
-
A.
tasteInfluence
chosen
Indicates how one entity’s characteristics, actions, or presence affect or shape another entity’s preferences, likes, or aesthetic tastes.
-
B.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
C.
tasteComparedTo
Indicates a comparison of the taste or flavor of one entity relative to another.
-
D.
leafTaste
Indicates that one entity has a particular taste or flavor associated with its leaves.
-
E.
aggravatedByTaste
Indicates that a condition, feeling, or reaction becomes worse or more intense due to a particular taste.
- 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_69f348ceb0a48190ae7feca263b6296c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 9:48 p.m.