Triple
T6469737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsimané people |
E142316
|
entity |
| Predicate | dietCharacteristic |
P3602
|
FINISHED |
| Object | high in fiber |
—
|
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: high in fiber | Statement: [Tsimané people, dietCharacteristic, high in fiber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dietCharacteristic Context triple: [Tsimané people, dietCharacteristic, high in fiber]
-
A.
dietVersion
Indicates that one diet is a specific version, variant, or iteration of another diet.
-
B.
dietaryOptions
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
C.
nutritionType
chosen
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
D.
characterizesDietAs
Indicates that one entity describes, defines, or assigns the type or nature of another entity’s diet.
-
E.
nutritionComponent
Indicates that one entity is a nutritional constituent, ingredient, or component of another (typically a food, diet, or nutritional product).
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a16272c81909313455002cd884d |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:50 p.m.