Triple
T38156071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Andrus |
E952888
|
entity |
| Predicate | aerialPhotographyBy |
P190147
|
FINISHED |
| Object | U.S. Navy |
—
|
NE NERFINISHED |
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: U.S. Navy | Statement: [Mount Andrus, aerialPhotographyBy, U.S. Navy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aerialPhotographyBy Context triple: [Mount Andrus, aerialPhotographyBy, U.S. Navy]
-
A.
aerialUnit
Indicates that the related entity functions as or is classified as an aerial unit, typically operating or acting in the air rather than on the ground or sea.
-
B.
usesImagery
Indicates that one entity employs descriptive or figurative language to create sensory or vivid mental images in relation to another entity or concept.
-
C.
photographsTakenIn
Indicates that photographs were captured or taken within a specific location or place.
-
D.
airbornePlatformFor
Indicates that one entity serves as an airborne platform or carrier used to support, transport, or deploy another entity.
-
E.
usesImageryOf
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another 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_69f76f0a67f4819080c492f61d688fcc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcb089a8f881909aa9e722babd43f7 |
completed | May 7, 2026, 3:32 p.m. |
| PD | Predicate disambiguation | batch_69fc45666c5c8190913bd632ac0e5b84 |
completed | May 7, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69fcb088aac481909db90804faff315f |
completed | May 7, 2026, 3:32 p.m. |
Created at: May 3, 2026, 4:21 p.m.