Triple
T37988046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temperate House, Royal Botanic Gardens, Kew |
E947748
|
entity |
| Predicate | costOfRestoration |
P4259
|
FINISHED |
| Object | about £41 million |
—
|
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: about £41 million | Statement: [Temperate House, Royal Botanic Gardens, Kew, costOfRestoration, about £41 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costOfRestoration Context triple: [Temperate House, Royal Botanic Gardens, Kew, costOfRestoration, about £41 million]
-
A.
estimatedCost
chosen
Indicates the predicted or calculated monetary amount expected to be required for something, such as a project, item, or action.
-
B.
restorationMeasure
Indicates that an action or intervention is undertaken to repair, rehabilitate, or return something to a previous or improved state.
-
C.
restorationReason
Indicates the reason or justification for which something that was previously removed, disabled, or altered has been restored to its former state.
-
D.
restorationType
Indicates the specific kind or category of restoration applied to an entity, such as the method, scope, or approach used to return it to a prior or improved state.
-
E.
restorationUse
Indicates the use of something specifically for the purpose of restoring, repairing, or returning another entity to a previous or improved state.
- 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_69f76ef8a1d08190a741bbbc5970e3b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc995dc2481908b3bd4217f8101e7 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.