Triple
T798508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sproul Hall |
E17074
|
entity |
| Predicate | exteriorMaterial |
P19176
|
FINISHED |
| Object | stone cladding |
—
|
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: stone cladding | Statement: [Sproul Hall, exteriorMaterial, stone cladding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exteriorMaterial Context triple: [Sproul Hall, exteriorMaterial, stone cladding]
-
A.
frontageMaterial
Indicates the material used on the exterior front-facing surface of a structure or property.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
hasFloorMaterial
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
D.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
E.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
- F. None of above. chosen
Provenance (4 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b4d9548190aad5fdf1211cf8cd |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5122a008190b0c621b7bc588d41 |
completed | March 1, 2026, 8:44 p.m. |
| PDg | Predicate description generation | batch_69a4a5bed20c81909ecc28bf42594e72 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:38 p.m.