Triple
T15491032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borba |
E378684
|
entity |
| Predicate | hasParish |
P35
|
FINISHED |
| Object | Borba (São Bartolomeu) |
E378684
|
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: Borba (São Bartolomeu) | Statement: [Borba, hasParish, Borba (São Bartolomeu)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borba (São Bartolomeu) Context triple: [Borba, hasParish, Borba (São Bartolomeu)]
-
A.
Borba Municipality
Borba Municipality is a local administrative region in Portugal’s Alentejo area, known for its wine production and marble quarries.
-
B.
Bonfim
Bonfim is a civil parish in the city of Porto, Portugal, known for its mix of historic neighborhoods and residential areas just east of the city center.
-
C.
Borba
chosen
Borba is a town and municipality in Portugal’s Alentejo region, noted for its wine production and marble quarries.
-
D.
Brejo de Beberibe
Brejo de Beberibe is a neighborhood within the city of Recife in the state of Pernambuco, Brazil.
-
E.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d48f17c819088c4d8c2d2b368c8 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 3:48 a.m.