Triple
T36636887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pitsenbarger statue in Piqua, Ohio |
E904487
|
entity |
| Predicate | honorsMilitaryRole |
P51002
|
FINISHED |
| Object | pararescueman |
—
|
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: pararescueman | Statement: [Pitsenbarger statue in Piqua, Ohio, honorsMilitaryRole, pararescueman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorsMilitaryRole Context triple: [Pitsenbarger statue in Piqua, Ohio, honorsMilitaryRole, pararescueman]
-
A.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
B.
formerMilitaryRole
Indicates that an entity previously held, but no longer holds, a specific military role or position.
-
C.
honorsRole
chosen
Indicates that one entity formally recognizes and respects the position, title, or role held by another entity.
-
D.
favoredMilitaryRole
Indicates the military position, function, or specialization that an entity prefers or is most inclined to choose.
-
E.
militaryRankTypicallyHeldBy
Indicates that a given military rank is most commonly or usually held by a particular type or category of person or position.
- 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_69f76e6c63e48190b1d0c3a79a6c7406 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.