Triple
T36333636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Bomber Command Centre Memorial Spire |
E894720
|
entity |
| Predicate | wingspanEquivalent |
P99340
|
FINISHED |
| Object | Avro Lancaster |
—
|
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: Avro Lancaster | Statement: [International Bomber Command Centre Memorial Spire, wingspanEquivalent, Avro Lancaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wingspanEquivalent Context triple: [International Bomber Command Centre Memorial Spire, wingspanEquivalent, Avro Lancaster]
-
A.
wingspan
Indicates the distance from the tip of one wing to the tip of the other wing when fully extended.
-
B.
wingLength
Indicates the length or measurement of a wing associated with an entity.
-
C.
wingSpanVariant
chosen
Indicates a relationship where one wing span measurement is a variant or alternative form of another wing span measurement.
-
D.
hasWingsMadeOf
Indicates that one entity has wings whose material or composition is made from the other entity.
-
E.
wingCount
Indicates the number of wings an entity possesses.
- 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_69f76e4e90148190b02fe52593c70b5b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7bb3ff1b08190802b1063d55d3923 |
completed | May 3, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a611a081908dd6aec1df3f4d7f |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.