Triple
T15488856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tocantins |
E377125
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Palmas |
E1160789
|
NE 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: Palmas | Statement: [Tocantins, hasCity, Palmas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palmas Context triple: [Tocantins, hasCity, Palmas]
-
A.
Palmas
chosen
Palmas is a planned city in central Brazil that serves as the administrative and political center of the state of Tocantins.
-
B.
Cascavel
Cascavel is a major city in western Paraná, Brazil, known as an important regional hub for agribusiness, commerce, and services.
-
C.
Cidade do Maio
Cidade do Maio is the main urban center and administrative capital of Maio Island in Cape Verde, known for its coastal setting and role as the island’s political and economic hub.
-
D.
Limeira
Limeira is a municipality in the interior of the Brazilian state of São Paulo, known for its industrial activity and history in the jewelry and citrus sectors.
-
E.
Brasília Teimosa
Brasília Teimosa is a coastal neighborhood in Recife, Brazil, known for its working-class roots, history of informal settlement, and vibrant seaside community.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03faaca588190b0397bc2e27a522a |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d4661088190bb53161247effcc4 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:48 a.m.