Triple
T4486083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 75th Ranger Regiment headquarters |
E107241
|
entity |
| Predicate | militaryUnitTypeServed |
P56843
|
FINISHED |
| Object | airborne 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: airborne light infantry | Statement: [75th Ranger Regiment headquarters, militaryUnitTypeServed, airborne light infantry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: militaryUnitTypeServed Context triple: [75th Ranger Regiment headquarters, militaryUnitTypeServed, airborne light infantry]
-
A.
placeOfMilitaryService
Indicates the location or institution where a person performed their military service.
-
B.
countryOfMilitaryService
Indicates that an entity served or is serving in the armed forces of a specified country.
-
C.
hasMilitaryBranch
Indicates that an entity is associated with, served in, or is part of a specific branch of a military organization.
-
D.
militaryBranchEligibility
Indicates that an entity meets the required conditions to serve in a specified branch of the military.
-
E.
militaryRole
Indicates the specific function, position, or duty an entity holds within a military organization or context.
- F. None of above. chosen
Provenance (4 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd556b93cc8190ab817d2817109a0b |
completed | March 20, 2026, 2:10 p.m. |
Created at: March 20, 2026, 12:59 p.m.