Triple
T11289096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward A. Carter Jr. |
E267275
|
entity |
| Predicate | hasMilitaryOccupationSpecialty |
P87507
|
FINISHED |
| Object | Infantryman |
—
|
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: Infantryman | Statement: [Edward A. Carter Jr., hasMilitaryOccupationSpecialty, Infantryman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryOccupationSpecialty Context triple: [Edward A. Carter Jr., hasMilitaryOccupationSpecialty, Infantryman]
-
A.
hasMilitarySpeciality
chosen
Indicates that an entity possesses a specific military role, skill set, or area of professional expertise within the armed forces.
-
B.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
C.
hasMilitaryDesignation
Indicates that an entity is assigned a specific military-related code, title, or classification.
-
D.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
E.
isMilitaryOfficer
Indicates that the subject holds an official position as an officer within 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98875a08190b8509fe55e49d52d |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.