Triple
T37338493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Baron |
E926962
|
entity |
| Predicate | laterMilitaryRole |
P71690
|
FINISHED |
| Object | observer in reconnaissance aircraft |
—
|
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: observer in reconnaissance aircraft | Statement: [Red Baron, laterMilitaryRole, observer in reconnaissance aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterMilitaryRole Context triple: [Red Baron, laterMilitaryRole, observer in reconnaissance aircraft]
-
A.
formerMilitaryRole
chosen
Indicates that an entity previously held, but no longer holds, a specific military role or position.
-
B.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
C.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
D.
favoredMilitaryRole
Indicates the military position, function, or specialization that an entity prefers or is most inclined to choose.
-
E.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0116ca6a1c81909a9e938dbe54eb8a |
completed | May 10, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_6a0116655e248190bdfe5b4bb4f1cf47 |
completed | May 10, 2026, 11:36 p.m. |
Created at: May 3, 2026, 4:16 p.m.