Triple
T11681743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Hampden, Buckinghamshire |
E277631
|
entity |
| Predicate | hasTraditionalRoofingMaterial |
P44342
|
FINISHED |
| Object | tile |
—
|
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: tile | Statement: [Great Hampden, Buckinghamshire, hasTraditionalRoofingMaterial, tile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalRoofingMaterial Context triple: [Great Hampden, Buckinghamshire, hasTraditionalRoofingMaterial, tile]
-
A.
hasTypeOfRoof
Indicates that an entity possesses or is characterized by a specific kind or style of roof.
-
B.
roofMaterialOriginal
chosen
Indicates the material that was originally used to construct the roof of a structure.
-
C.
buildingMaterialTradition
Indicates the customary or historically established use of particular materials in the construction of a building or structure.
-
D.
traditionallyBuiltOver
Indicates that one entity has been constructed on top of another in a manner consistent with long-established or customary building practices.
-
E.
hasRoofShape
Indicates that one entity possesses or is characterized by a specific shape or form of roof.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a462bb2881909238107d34c0a28d |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.