Triple
T17250932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airman |
E418748
|
entity |
| Predicate | hasHardcoverEdition |
P10512
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Airman, hasHardcoverEdition, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHardcoverEdition Context triple: [Airman, hasHardcoverEdition, yes]
-
A.
hasYoungReadersEdition
Indicates that a work has a specially adapted edition intended for young or juvenile readers.
-
B.
hasEditionIn
Indicates that one entity has a specific edition or version that exists or is available in another entity (such as a particular format, language, or location).
-
C.
hasAnthologyFormat
Indicates that an entity is presented or structured in the form of an anthology (a collection of distinct works or pieces).
-
D.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
E.
hasCoverType
chosen
Indicates that one entity possesses or is associated with a specific type or category of cover.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e270fc48190a75f3893a5ec059b |
completed | April 19, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.