Triple
T1487717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avro Lancaster |
E29504
|
entity |
| Predicate | preservedExamples |
P1259
|
FINISHED |
| Object | several museum aircraft worldwide |
—
|
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: several museum aircraft worldwide | Statement: [Avro Lancaster, preservedExamples, several museum aircraft worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preservedExamples Context triple: [Avro Lancaster, preservedExamples, several museum aircraft worldwide]
-
A.
hasExample
chosen
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
B.
preservedAt
Indicates that something is kept, maintained, or conserved in a particular place or context.
-
C.
workPreservedIn
Indicates that a work is maintained, stored, or archived within a particular medium, collection, or repository so that it remains accessible over time.
-
D.
preservationMethod
Indicates the technique or process used to maintain, protect, or prolong the condition, quality, or usability of something over time.
-
E.
stateOfPreservation
Indicates the condition or degree to which something has been maintained, conserved, or kept intact over time.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6a44efc819084254614d8ea4669 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c486eacc81909c272f9bdf50a7c3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.