Triple
T19113478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camp Frank D. Merrill |
E467847
|
entity |
| Predicate | militarySpecialtyTrained |
P87507
|
FINISHED |
| Object | light infantry |
—
|
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: light infantry | Statement: [Camp Frank D. Merrill, militarySpecialtyTrained, light infantry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militarySpecialtyTrained Context triple: [Camp Frank D. Merrill, militarySpecialtyTrained, light infantry]
-
A.
hasMilitarySpeciality
chosen
Indicates that an entity possesses a specific military role, skill set, or area of professional expertise within the armed forces.
-
B.
militaryBackground
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
C.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
D.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
-
E.
militaryBranchSupervised
Indicates that one military branch has authority over, or is responsible for overseeing and directing, another military branch.
- 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e39617408190b5134918f54f9c52 |
completed | April 20, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e4b9ac41848190afd0f33b42cebe99 |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:05 p.m.