Triple
T924291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | António Costa |
E19948
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Fernanda Tadeu
Fernanda Tadeu is a Portuguese educator and public figure best known as the wife of former Prime Minister António Costa.
|
E118400
|
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: Fernanda Tadeu | Statement: [António Costa, spouse, Fernanda Tadeu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fernanda Tadeu Context triple: [António Costa, spouse, Fernanda Tadeu]
-
A.
Luciana Barroso
Luciana Barroso is an Argentine former bartender and flight attendant best known as the wife of American actor Matt Damon.
-
B.
Maria Azevêdo
Maria Azevêdo is known as the wife of Brazilian diplomat Roberto Azevêdo, former Director-General of the World Trade Organization.
-
C.
Manuela Veloso
Manuela Veloso is a prominent computer scientist and roboticist known for her pioneering work in artificial intelligence and multi-agent robotics.
-
D.
Vera Lúcia Cabreira
Vera Lúcia Cabreira was the wife of renowned Brazilian architect Oscar Niemeyer.
-
E.
Isabel Barreto
Isabel Barreto was a late 16th-century Spanish navigator and colonial figure often regarded as one of the first known female admirals in history, noted for her role in Pacific exploration.
- 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: Fernanda Tadeu Triple: [António Costa, spouse, Fernanda Tadeu]
Generated description
Fernanda Tadeu is a Portuguese educator and public figure best known as the wife of former Prime Minister António Costa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fernanda Tadeu Target entity description: Fernanda Tadeu is a Portuguese educator and public figure best known as the wife of former Prime Minister António Costa.
-
A.
Luciana Barroso
Luciana Barroso is an Argentine former bartender and flight attendant best known as the wife of American actor Matt Damon.
-
B.
Maria Azevêdo
Maria Azevêdo is known as the wife of Brazilian diplomat Roberto Azevêdo, former Director-General of the World Trade Organization.
-
C.
Manuela Veloso
Manuela Veloso is a prominent computer scientist and roboticist known for her pioneering work in artificial intelligence and multi-agent robotics.
-
D.
Vera Lúcia Cabreira
Vera Lúcia Cabreira was the wife of renowned Brazilian architect Oscar Niemeyer.
-
E.
Isabel Barreto
Isabel Barreto was a late 16th-century Spanish navigator and colonial figure often regarded as one of the first known female admirals in history, noted for her role in Pacific exploration.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3296f50819087f809fbe90b139e |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a0d31e8819091d3402546d8fa33 |
completed | March 7, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_69ac2a7b1a148190950d40db59a6c0de |
completed | March 7, 2026, 1:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac2ad8a14c819086d21ba068aedf2f |
completed | March 7, 2026, 1:40 p.m. |
Created at: March 1, 2026, 7:40 p.m.