Triple
T10566984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Ángeles, Chile |
E249374
|
entity |
| Predicate | hasNearbyAgriculturalProduction |
P93890
|
FINISHED |
| Object | grains |
—
|
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: grains | Statement: [Los Ángeles, Chile, hasNearbyAgriculturalProduction, grains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyAgriculturalProduction Context triple: [Los Ángeles, Chile, hasNearbyAgriculturalProduction, grains]
-
A.
hasNearbyAgriculturalActivity
chosen
Indicates that an entity is located close enough to agricultural operations or land use for those activities to be considered relevant or influential to it.
-
B.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
C.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
D.
locatedInAgriculturalRegion
Indicates that an entity is situated within a region primarily characterized by agricultural activities or land use.
-
E.
isAgriculturalCity
Indicates that a city is primarily characterized by agriculture-based activities, economy, or land use.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:36 p.m.