Triple
T24465436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 367-80 |
E616954
|
entity |
| Predicate | fuselageDesignBasisFor |
P156197
|
FINISHED |
| Object | Boeing 707 |
—
|
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: Boeing 707 | Statement: [Boeing 367-80, fuselageDesignBasisFor, Boeing 707]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuselageDesignBasisFor Context triple: [Boeing 367-80, fuselageDesignBasisFor, Boeing 707]
-
A.
fuselageType
Indicates the specific structural or design category of an aircraft’s fuselage that an entity belongs to or uses.
-
B.
fuselageVariant
Indicates that one fuselage is a specific version or variant derived from another fuselage design.
-
C.
fuselageLength_m
Indicates the measured length of an aircraft’s fuselage, expressed in meters.
-
D.
fuselageShape
Indicates the geometric form or contour of an object's fuselage, describing how its main body is shaped.
-
E.
fuselageLengthComparedTo
Indicates how the length of one fuselage compares to the length of another fuselage, typically in terms of being longer, shorter, or equal.
- 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_69e2d7f197588190889a03e620558059 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f298cd2a748190bbb4634e879d89f2 |
completed | April 29, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69f287d76c7c81909494f12e606a9149 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:19 a.m.