Triple
T1202234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire Lee Chennault |
E25807
|
entity |
| Predicate | hasPartInMottoOrSlogan |
P14561
|
FINISHED |
| Object | advocacy of pursuit aviation and air defense strategies |
—
|
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: advocacy of pursuit aviation and air defense strategies | Statement: [Claire Lee Chennault, hasPartInMottoOrSlogan, advocacy of pursuit aviation and air defense strategies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInMottoOrSlogan Context triple: [Claire Lee Chennault, hasPartInMottoOrSlogan, advocacy of pursuit aviation and air defense strategies]
-
A.
hasPartInMotto
chosen
Indicates that something is included as a component or element within a motto.
-
B.
isMottoOf
Indicates that a phrase or expression serves as the official motto associated with a particular entity.
-
C.
mottoOriginalLanguage
Indicates the language in which a motto was originally formulated or expressed.
-
D.
associatedWithFamousSlogan
Indicates that an entity is connected to, known for, or commonly linked with a particular famous slogan.
-
E.
hasMottoInText
Indicates that an entity has a motto expressed in a specific textual form or wording.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbda0b081909c0147121a945e27 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.