Triple
T15228597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magallanes, Cavite |
E363939
|
entity |
| Predicate | agriculturalArea |
P24310
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Magallanes, Cavite, agriculturalArea, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agriculturalArea Context triple: [Magallanes, Cavite, agriculturalArea, true]
-
A.
locatedInAgriculturalRegion
chosen
Indicates that an entity is situated within a region primarily characterized by agricultural activities or land use.
-
B.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
C.
agriculturalFocus
Indicates that an entity is primarily concerned with, oriented toward, or specializing in agriculture or farming-related activities.
-
D.
connectsToAgriculturalRegion
Indicates a relationship where something is linked or associated with an agricultural region, such as through proximity, infrastructure, or functional interaction.
-
E.
agriculturalEnvironment
Indicates that something exists in, is associated with, or is influenced by an agricultural or farming-related 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078ccdf48190b34eabd9e24e45a1 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.