Triple
T22630019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DEKALB |
E558521
|
entity |
| Predicate | focusTrait |
P148992
|
FINISHED |
| Object | yield potential |
—
|
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: yield potential | Statement: [DEKALB, focusTrait, yield potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusTrait Context triple: [DEKALB, focusTrait, yield potential]
-
A.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
B.
focusFeature
Indicates that one entity is the primary or emphasized feature, aspect, or attribute being highlighted or concentrated on in relation to another.
-
C.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
-
D.
focusTheory
Indicates that one entity serves as the primary theoretical framework, perspective, or model that another entity is based on, organized around, or chiefly concerned with.
-
E.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
- 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17008e7648190b243c18067b4efb9 |
completed | April 29, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
| PDg | Predicate description generation | batch_69ee8841e9cc81908d23b34215e3be71 |
completed | April 26, 2026, 9:48 p.m. |
Created at: April 17, 2026, 3:02 p.m.