Triple
T5906434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 720 |
E131350
|
entity |
| Predicate | hasWingFeature |
P7143
|
FINISHED |
| Object | modified wing with inboard Krueger flaps |
—
|
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: modified wing with inboard Krueger flaps | Statement: [Boeing 720, hasWingFeature, modified wing with inboard Krueger flaps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWingFeature Context triple: [Boeing 720, hasWingFeature, modified wing with inboard Krueger flaps]
-
A.
hasWings
Indicates that an entity possesses wings as physical appendages.
-
B.
hasWingConfiguration
chosen
Indicates how an entity’s wings are arranged, structured, or configured relative to its body or to each other.
-
C.
hasHostWing
Indicates that one entity serves as the host structure or supporting wing for another entity.
-
D.
hasNumberOfLeftWings
Indicates the quantity of left wings that an entity possesses.
-
E.
hasArmedWing
Indicates that an entity maintains, controls, or is associated with an organized armed or military wing.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.