Triple
T6985589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albatros D.III |
E161951
|
entity |
| Predicate | structuralIssue |
P41290
|
FINISHED |
| Object | lower wing failures in early service |
—
|
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: lower wing failures in early service | Statement: [Albatros D.III, structuralIssue, lower wing failures in early service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: structuralIssue Context triple: [Albatros D.III, structuralIssue, lower wing failures in early service]
-
A.
designIssue
chosen
Indicates that there is a problem, flaw, or concern related to the design of an entity or system.
-
B.
affectedStructure
Indicates that one entity is the structure, component, or part that is impacted, altered, or influenced by another entity or event.
-
C.
underlyingIssue
Indicates that one situation, problem, or condition is the fundamental cause or root problem behind another.
-
D.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
E.
architecturalIntegrity
Indicates that an entity maintains the coherence, stability, and consistency of its overall structural or design framework without compromising essential components or principles.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dbbd926c8190a8b60527bd553fa3 |
completed | March 27, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c4a18881908d267137daed828b |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.