Triple
T12312411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itu |
E293512
|
entity |
| Predicate | distanceFromSãoPaulo |
P43610
|
FINISHED |
| Object | about 100 km |
—
|
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: about 100 km | Statement: [Itu, distanceFromSãoPaulo, about 100 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSãoPaulo Context triple: [Itu, distanceFromSãoPaulo, about 100 km]
-
A.
distanceToSãoPaulo
chosen
Indicates the spatial distance between a given entity’s location and the city of São Paulo.
-
B.
distanceToBeloHorizonte
Indicates the spatial distance between an entity and the location of Belo Horizonte.
-
C.
distanceToRioDeJaneiroCity
Indicates the physical distance between a given entity’s location and the city of Rio de Janeiro.
-
D.
distanceToFlorianopolisApproxKm
Indicates an approximate distance, measured in kilometers, between a given entity and Florianópolis.
-
E.
distanceToMaceio
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Maceió.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec02c008190a56aae60a3d9eff6 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.