Triple
T13968338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Army Signal Regiment units |
E335984
|
entity |
| Predicate | typicalPersonnelSpecialty |
P466
|
FINISHED |
| Object | signal officers |
—
|
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: signal officers | Statement: [U.S. Army Signal Regiment units, typicalPersonnelSpecialty, signal officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPersonnelSpecialty Context triple: [U.S. Army Signal Regiment units, typicalPersonnelSpecialty, signal officers]
-
A.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
-
B.
personnel
Indicates that an entity serves as staff or workforce associated with another entity, such as an organization, project, or facility.
-
C.
professionServed
Indicates that an entity has performed work or provided services in a particular profession or occupational role.
-
D.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
E.
peakPersonnel
Indicates the maximum number of personnel involved or present at any point during a specified period or activity.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8daeac8190aadd4b3b60222482 |
completed | April 14, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69dd465a21408190b912a42c50ffa0d9 |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.