Triple
T7472692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AR |
E176545
|
entity |
| Predicate | usedAlongWith |
P4791
|
FINISHED |
| Object | United States country name |
—
|
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: United States country name | Statement: [AR, usedAlongWith, United States country name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAlongWith Context triple: [AR, usedAlongWith, United States country name]
-
A.
usedWith
chosen
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
B.
associatedWithUse
Indicates a relationship where one entity is connected to or involved in the use or utilization of another entity.
-
C.
usedInformallyAlongside
Indicates that something is employed in an informal, non-standard way together with or in addition to something else.
-
D.
alsoUsedIn
Indicates that something is additionally employed, applied, or present in another context, setting, or use case beyond the primary one.
-
E.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
- 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_69c69f223fd88190b4c69b95d7cbeeda |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f416d018819098275cc51d8def3f |
completed | March 27, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69c6f03d967081908a8e696ff9693b90 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:41 p.m.