Triple
T1169977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Recife |
E24891
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Jordão
Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
|
E141506
|
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: Jordão | Statement: [Recife, hasPart, Jordão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jordão Context triple: [Recife, hasPart, Jordão]
-
A.
Alcântara
Alcântara is a historic coastal municipality in the Brazilian state of Maranhão, known for its preserved colonial architecture and proximity to the Alcântara Launch Center.
-
B.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
-
C.
Gilão River
The Gilão River is a waterway in Portugal’s Algarve region that flows through the historic town of Tavira before reaching the Atlantic Ocean.
-
D.
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.
-
E.
Rio Hato
Rio Hato is a coastal area in Panama known for its airfield, which was a key target during the U.S. invasion of Panama in Operation Just Cause.
- 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: Jordão Triple: [Recife, hasPart, Jordão]
Generated description
Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jordão Target entity description: Jordão is a neighborhood of Recife, Brazil, known as a largely residential area on the city’s outskirts.
-
A.
Alcântara
Alcântara is a historic coastal municipality in the Brazilian state of Maranhão, known for its preserved colonial architecture and proximity to the Alcântara Launch Center.
-
B.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
-
C.
Gilão River
The Gilão River is a waterway in Portugal’s Algarve region that flows through the historic town of Tavira before reaching the Atlantic Ocean.
-
D.
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.
-
E.
Rio Hato
Rio Hato is a coastal area in Panama known for its airfield, which was a key target during the U.S. invasion of Panama in Operation Just Cause.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bce821b481908bc278a3fa7973f4 |
completed | March 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8a0646388190b440451d786db04c |
completed | March 7, 2026, 8:26 p.m. |
| NEDg | Description generation | batch_69ac8ccae06c81909704cdf102dcc7dd |
completed | March 7, 2026, 8:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac8d2ee740819081369787bbf1ef93 |
completed | March 7, 2026, 8:40 p.m. |
Created at: March 1, 2026, 7:45 p.m.