Triple
T23993764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bijagó |
E605135
|
entity |
| Predicate | agriculturalPractices |
P4104
|
FINISHED |
| Object | swidden rice farming |
—
|
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: swidden rice farming | Statement: [Bijagó, agriculturalPractices, swidden rice farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalPractices Context triple: [Bijagó, agriculturalPractices, swidden rice farming]
-
A.
agriculturalPractice
chosen
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
B.
agriculturalFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
-
C.
agricultureUse
Indicates that something is used for, involved in, or designated for agricultural activities or purposes.
-
D.
usedAgriculture
Indicates that an entity employed agricultural methods, practices, or resources for cultivation, production, or related purposes.
-
E.
agriculturalImplication
Indicates a relationship where one factor, event, or condition has consequences, effects, or relevance specifically within an agricultural context.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38dbf78819081826f86bf578069 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:38 p.m.