Triple
T3650490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tequesta |
E77405
|
entity |
| Predicate | usedAgriculture |
P50683
|
FINISHED |
| Object | limited or no agriculture |
—
|
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: limited or no agriculture | Statement: [Tequesta, usedAgriculture, limited or no agriculture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAgriculture Context triple: [Tequesta, usedAgriculture, limited or no agriculture]
-
A.
agriculturalPractice
Indicates a relationship where an entity engages in, applies, or is associated with a specific method or technique of agriculture or farming.
-
B.
representsAgriculture
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to another entity.
-
C.
agriculturalRole
Indicates a role or function that an entity has within agricultural activities, production, or systems.
-
D.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
E.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc39303bc819090725643e53a96d6 |
completed | March 8, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69adb84650148190bf79231105e58d7f |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adbae14d488190a6024548979c6faf |
completed | March 8, 2026, 6:07 p.m. |
Created at: March 8, 2026, 3:24 p.m.