Triple
T17758075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bell X-1E |
E443296
|
entity |
| Predicate | primaryTestFocus |
P815
|
FINISHED |
| Object | high Mach number aerodynamics |
—
|
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: high Mach number aerodynamics | Statement: [Bell X-1E, primaryTestFocus, high Mach number aerodynamics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTestFocus Context triple: [Bell X-1E, primaryTestFocus, high Mach number aerodynamics]
-
A.
primaryTextualFocus
Indicates that one entity is the main subject or central topic emphasized within the text of another entity.
-
B.
primaryTarget
chosen
Indicates that an entity is the main or most important target of another entity’s action, focus, or effect.
-
C.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
D.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
E.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841fe97881908f4df503fb781763 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:10 a.m.