Triple
T4067795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shilton |
E86366
|
entity |
| Predicate | buildingMaterialCommonlyUsed |
P29245
|
FINISHED |
| Object | local stone |
—
|
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: local stone | Statement: [Shilton, buildingMaterialCommonlyUsed, local stone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingMaterialCommonlyUsed Context triple: [Shilton, buildingMaterialCommonlyUsed, local stone]
-
A.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
B.
buildingMaterialTradition
chosen
Indicates the customary or historically established use of particular materials in the construction of a building or structure.
-
C.
wallMaterial
Indicates that one entity is the material from which a wall or walls of another entity are constructed.
-
D.
ceilingMaterial
Indicates the material from which a ceiling is constructed or finished.
-
E.
widelyUsedIn
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf73a1c81909f1741f4ecf55f98 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.