Triple
T24505339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belize–Mexico border |
E618049
|
entity |
| Predicate | hasNearbySettlementInBelize |
P3883
|
FINISHED |
| Object | Santa Elena |
—
|
NE NERFINISHED |
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: Santa Elena | Statement: [Belize–Mexico border, hasNearbySettlementInBelize, Santa Elena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbySettlementInBelize Context triple: [Belize–Mexico border, hasNearbySettlementInBelize, Santa Elena]
-
A.
distanceFromBelizeMainland
Indicates the measured spatial distance separating a given entity from the mainland territory of Belize.
-
B.
hasTribalHeadquartersNearby
Indicates that the subject entity is located close to the tribal headquarters of a Native nation or tribe.
-
C.
hasNearbySettlementDensity
Indicates that an entity is associated with a concentration of settlements located within a nearby surrounding area.
-
D.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
E.
hasNearbyTown
chosen
Indicates that one location has a town situated close to it in geographic proximity.
- 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_69e2d7f682108190a1a7ca5fd485ee8a |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:23 a.m.