Triple
T9409579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lambay Castle |
E226670
|
entity |
| Predicate | hasDesignElements |
P1529
|
FINISHED |
| Object | whitewashed walls |
—
|
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: whitewashed walls | Statement: [Lambay Castle, hasDesignElements, whitewashed walls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignElements Context triple: [Lambay Castle, hasDesignElements, whitewashed walls]
-
A.
hasDesign
chosen
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
hasDesignOption
Indicates that an entity is associated with or offers a particular design alternative or configurable design choice.
-
C.
hasStageDesignElement
Indicates a relationship in which a stage production, performance, or set includes or is associated with a particular stage design element (such as props, scenery, lighting, or other visual components).
-
D.
hasDesignIntent
Indicates that one entity embodies or reflects the planned purpose, function, or conceptual intent defined by another entity.
-
E.
hasDesignConsideration
Indicates that one entity takes another entity into account as a factor, constraint, or requirement in its design or planning.
- 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_69ca843280488190bc65600e843ef9e6 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd52547f0c81908ed4f53b9f05ebaa |
completed | April 1, 2026, 5:13 p.m. |
| PD | Predicate disambiguation | batch_69cca54c37f88190bddccf28e5fe5c84 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:47 p.m.