Triple
T29747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mojave people |
E593
|
entity |
| Predicate | traditionalCrop |
P1897
|
FINISHED |
| Object | corn |
—
|
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: corn | Statement: [Mojave people, traditionalCrop, corn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalCrop Context triple: [Mojave people, traditionalCrop, corn]
-
A.
majorCrop
chosen
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
-
B.
traditionalCuisine
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
C.
hasSoil
Indicates that one entity possesses, contains, or is associated with a particular type or instance of soil.
-
D.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a2490019948190a89bb0910c60d462 |
completed | Feb. 28, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69a2486d40348190b2d21fc444f499a6 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.