Triple
T2672632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgetown Historic District |
E55780
|
entity |
| Predicate | streetMaterial |
P41604
|
FINISHED |
| Object | cobblestone |
—
|
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: cobblestone | Statement: [Georgetown Historic District, streetMaterial, cobblestone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetMaterial Context triple: [Georgetown Historic District, streetMaterial, cobblestone]
-
A.
hasFloorMaterial
Indicates that an entity’s floor is made of, covered with, or constructed from a specified material.
-
B.
exteriorMaterial
Indicates the material that forms the outer surface or outer construction of an object or structure.
-
C.
wallMaterial
Indicates that one entity is the material from which a wall or walls of another entity are constructed.
-
D.
frontageMaterial
Indicates the material used on the exterior front-facing surface of a structure or property.
-
E.
floorType
Indicates the type or material classification of a floor associated with an 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd98f98908190b5c6fb38d3d4367a |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8f98c348190a68064c565589459 |
completed | March 7, 2026, 7:51 a.m. |
Created at: March 6, 2026, 9:54 p.m.