Triple
T22143886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recife metropolitan region |
E547234
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Itaquitinga
Itaquitinga is a municipality in the Brazilian state of Pernambuco that forms part of the Recife metropolitan area.
|
E1522013
|
NE FINISHED |
How this triple was built (4 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: Itaquitinga | Statement: [Recife metropolitan region, hasMunicipality, Itaquitinga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itaquitinga Context triple: [Recife metropolitan region, hasMunicipality, Itaquitinga]
-
A.
Itauguá
Itauguá is a Paraguayan city known for its traditional ñandutí lacework and cultural heritage, located in the Central Department near Asunción.
-
B.
Cibiru
Cibiru is a district in the eastern part of Bandung, West Java, Indonesia, known for its educational institutions and growing urban residential areas.
-
C.
Reritiba
Reritiba is a historic locality in Brazil, known as the place where the Jesuit missionary and saint José de Anchieta died.
-
D.
Mongaguá
Mongaguá is a coastal municipality in the state of São Paulo, Brazil, known for its beaches and tourism along the Atlantic Ocean.
-
E.
Tucurú
Tucurú is a municipality and town located in the Alta Verapaz Department of central Guatemala, known for its rural setting and agricultural activities.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Itaquitinga Triple: [Recife metropolitan region, hasMunicipality, Itaquitinga]
Generated description
Itaquitinga is a municipality in the Brazilian state of Pernambuco that forms part of the Recife metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Itaquitinga Target entity description: Itaquitinga is a municipality in the Brazilian state of Pernambuco that forms part of the Recife metropolitan area.
-
A.
Itauguá
Itauguá is a Paraguayan city known for its traditional ñandutí lacework and cultural heritage, located in the Central Department near Asunción.
-
B.
Cibiru
Cibiru is a district in the eastern part of Bandung, West Java, Indonesia, known for its educational institutions and growing urban residential areas.
-
C.
Reritiba
Reritiba is a historic locality in Brazil, known as the place where the Jesuit missionary and saint José de Anchieta died.
-
D.
Mongaguá
Mongaguá is a coastal municipality in the state of São Paulo, Brazil, known for its beaches and tourism along the Atlantic Ocean.
-
E.
Tucurú
Tucurú is a municipality and town located in the Alta Verapaz Department of central Guatemala, known for its rural setting and agricultural activities.
- F. None of above. chosen
Provenance (5 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129c045448190b3d189cdb8c0d2fd |
completed | April 28, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a96fe404481908a6b27dcf1406dfb |
completed | May 18, 2026, 4:35 a.m. |
| NEDg | Description generation | batch_6a0a97e509a88190a7f316cf340d010a |
completed | May 18, 2026, 4:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a987daa208190bab5b7adec1913e8 |
completed | May 18, 2026, 4:41 a.m. |
Created at: April 16, 2026, 8:32 p.m.