Triple
T34495508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Checkerboard Hill |
E885594
|
entity |
| Predicate | hasManMadeMarking |
P203582
|
FINISHED |
| Object | checkerboard navigation aid |
—
|
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: checkerboard navigation aid | Statement: [Checkerboard Hill, hasManMadeMarking, checkerboard navigation aid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasManMadeMarking Context triple: [Checkerboard Hill, hasManMadeMarking, checkerboard navigation aid]
-
A.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
-
B.
hasFloorMarkings
Indicates that an entity features visible markings or lines on its floor surface, typically used for guidance, organization, or safety.
-
C.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
D.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
E.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
- 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_69f349cafcec8190997b45b3fdc16c27 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a01a9e333fc819087d583ff319be0b3 |
completed | May 11, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_6a01a877c9e08190b0678618d3533286 |
completed | May 11, 2026, 9:59 a.m. |
| PDg | Predicate description generation | batch_6a01a9e27adc81908b90db24e93f3be0 |
completed | May 11, 2026, 10:05 a.m. |
Created at: May 1, 2026, 2:01 a.m.