Triple
T422833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Nevada (BB-36) |
E8140
|
entity |
| Predicate | paintScheme_Operation Crossroads |
P13565
|
FINISHED |
| Object | bright orange |
—
|
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: bright orange | Statement: [USS Nevada (BB-36), paintScheme_Operation Crossroads, bright orange]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paintScheme_Operation Crossroads Context triple: [USS Nevada (BB-36), paintScheme_Operation Crossroads, bright orange]
-
A.
hasCrossColor
Indicates that an entity possesses a cross-shaped marking or pattern of a specified color.
-
B.
crossWith
Indicates that one entity intersects or passes over/through the path, boundary, or position of another entity.
-
C.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
D.
crossedBy
Indicates that one entity (typically a path, line, or boundary) is intersected or traversed by another entity.
-
E.
crossesSectionOf
Indicates that one entity passes through or over a specific segment or portion of 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec200648190bcb9f1b98c8e9cdf |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.