Triple
T25289791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Confederate Kennesaw Mountain line |
E634047
|
entity |
| Predicate | frontFacing |
P1699
|
FINISHED |
| Object | Union lines to the northwest and west |
—
|
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: Union lines to the northwest and west | Statement: [Confederate Kennesaw Mountain line, frontFacing, Union lines to the northwest and west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontFacing Context triple: [Confederate Kennesaw Mountain line, frontFacing, Union lines to the northwest and west]
-
A.
frontCameraFeature
Indicates that an entity has a specified feature, capability, or characteristic associated with its front-facing camera.
-
B.
front
chosen
Indicates that one entity is located directly before or facing another entity along a primary viewing or movement direction.
-
C.
frontOf
Indicates that one entity is positioned directly before another along a primary viewing or movement direction.
-
D.
frontIn
Indicates that one entity is positioned directly in front of another entity in space or sequence.
-
E.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f48e0c2aa88190aca9e47be7138854 |
completed | May 1, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69f45d06d0388190b36ecde92013624a |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 21, 2026, 1:21 p.m.