Triple
T35668024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenida Francisco Matarazzo |
E1030626
|
entity |
| Predicate | hasOfficialLanguageOfToponym |
P189481
|
FINISHED |
| Object | Portuguese |
—
|
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: Portuguese | Statement: [Avenida Francisco Matarazzo, hasOfficialLanguageOfToponym, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialLanguageOfToponym Context triple: [Avenida Francisco Matarazzo, hasOfficialLanguageOfToponym, Portuguese]
-
A.
hasLanguageOfToponym
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
hasOfficialLanguageOfLocation
Indicates that a location has a specified language recognized as its official language.
-
C.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
D.
declaresOfficialLanguageOf
Indicates that an authority formally designates a particular language as the official language of a specified entity or jurisdiction.
-
E.
hasWritingSystemOfToponym
Indicates that a toponym is written or represented using a particular writing system.
- F. None of above. chosen
Provenance (4 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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc36bcac48190a726b40442c094d1 |
completed | May 6, 2026, 10:40 p.m. |
Created at: May 3, 2026, 4:05 p.m.