Triple
T11412421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Checkerboard Division |
E270403
|
entity |
| Predicate | hasShoulderPatchShape |
P99173
|
FINISHED |
| Object | square checkerboard design |
—
|
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: square checkerboard design | Statement: [Checkerboard Division, hasShoulderPatchShape, square checkerboard design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoulderPatchShape Context triple: [Checkerboard Division, hasShoulderPatchShape, square checkerboard design]
-
A.
hasShoulderButtons
Indicates that an object, typically a device or controller, includes buttons positioned on its shoulders or top side edges.
-
B.
hasEmergencyShoulder
Indicates that a roadway segment includes an emergency shoulder area intended for stopped or disabled vehicles.
-
C.
hasSideArch
Indicates that one entity possesses or features a secondary or lateral arch structure in relation to another entity.
-
D.
shoulderHeightRange
Indicates the range of vertical height measured from the ground to an entity’s shoulders.
-
E.
hasTypicalSleeveStyle
Indicates the usual or characteristic sleeve design associated with an item, such as a garment or uniform.
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d801acd9bc81908a23b1b7b4e778d3 |
completed | April 9, 2026, 7:44 p.m. |
| PD | Predicate disambiguation | batch_69d7e70ffd708190b62a78ebcbce9f78 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:34 p.m.