Triple
T7601221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Army Armor Branch |
E179986
|
entity |
| Predicate | associatedMOS |
P78117
|
FINISHED |
| Object | 19K |
—
|
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: 19K | Statement: [United States Army Armor Branch, associatedMOS, 19K]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedMOS Context triple: [United States Army Armor Branch, associatedMOS, 19K]
-
A.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
B.
associatedWithMatch
Indicates a relationship where an entity is linked or connected to a particular match or matching event.
-
C.
associatedSingle
Indicates a one-to-one association where an entity is linked to exactly one corresponding related entity.
-
D.
associatedConsort
Indicates a spousal or consort relationship linking one entity to another as their partner.
-
E.
associatedModalityGroup
Indicates a relationship where something is linked to, or grouped under, a specific modality category or set of modalities.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9d9c55c8190841f3bf3225c096a |
completed | March 27, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e2e42c8190afc802c4796c9cc2 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8184bb08190b2f70545a6aa277c |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:54 p.m.