Triple
T1043837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing X-48 |
E22529
|
entity |
| Predicate | researchObjective |
P7242
|
FINISHED |
| Object | improved lift-to-drag ratio |
—
|
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: improved lift-to-drag ratio | Statement: [Boeing X-48, researchObjective, improved lift-to-drag ratio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: researchObjective Context triple: [Boeing X-48, researchObjective, improved lift-to-drag ratio]
-
A.
educationalObjective
Indicates the intended learning goal, skill, or competency that an educational resource, activity, or program is designed to achieve.
-
B.
scienceGoals
chosen
Indicates the objectives or intended outcomes that guide and justify a scientific activity, project, or investigation.
-
C.
researchProgram
Indicates that an entity is engaged in, associated with, or part of a structured research initiative or program.
-
D.
researchContext
Indicates the situational, methodological, or thematic setting within which a particular piece of research is conducted or interpreted.
-
E.
trainingObjective
Indicates the goal or target outcome that a training process is designed to achieve.
- F. None of above.
Provenance (3 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8475ab48190848388eea6448cb6 |
completed | March 1, 2026, 10:05 p.m. |
| PD | Predicate disambiguation | batch_69a4b72ba60881908b017ef3b2b9645e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.