Triple
T15689091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Horn |
E380277
|
entity |
| Predicate | trimFocus |
P119770
|
FINISHED |
| Object | value-oriented feature upgrade over base trim |
—
|
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: value-oriented feature upgrade over base trim | Statement: [Big Horn, trimFocus, value-oriented feature upgrade over base trim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trimFocus Context triple: [Big Horn, trimFocus, value-oriented feature upgrade over base trim]
-
A.
importFocus
Indicates that attention, priority, or emphasis is being brought into or concentrated on a particular entity or aspect.
-
B.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
-
C.
lessFocusOn
Indicates that one entity directs reduced attention, emphasis, or priority toward another entity or activity compared to alternatives.
-
D.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4cee5481908699fbb2b7bdd2f6 |
completed | April 16, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:44 a.m.