Triple
T4100286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Estrada |
E87923
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Estrada
Estrada is a Filipino surname most prominently associated with Joseph Estrada, a former movie actor who became the 13th President of the Philippines.
|
E412838
|
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: Estrada | Statement: [Joseph Estrada, familyName, Estrada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Estrada Context triple: [Joseph Estrada, familyName, Estrada]
-
A.
Cardoso
Cardoso is a common Portuguese-language surname borne by numerous individuals, including prominent Brazilian political and cultural figures.
-
B.
Gamboa
Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
-
C.
Rojas
Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
-
D.
Tostão
Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
-
E.
O’Donojú
O’Donojú is the surname of Juan O’Donojú, the last Spanish political chief of New Spain who played a key role in Mexico’s transition to independence.
- 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: Estrada Triple: [Joseph Estrada, familyName, Estrada]
Generated description
Estrada is a Filipino surname most prominently associated with Joseph Estrada, a former movie actor who became the 13th President of the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Estrada Target entity description: Estrada is a Filipino surname most prominently associated with Joseph Estrada, a former movie actor who became the 13th President of the Philippines.
-
A.
Cardoso
Cardoso is a common Portuguese-language surname borne by numerous individuals, including prominent Brazilian political and cultural figures.
-
B.
Gamboa
Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
-
C.
Rojas
Rojas is a Spanish surname historically associated with prominent noble families and political figures in Spain.
-
D.
Tostão
Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
-
E.
O’Donojú
O’Donojú is the surname of Juan O’Donojú, the last Spanish political chief of New Spain who played a key role in Mexico’s transition to independence.
- 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_69aed94564cc8190a9c1457daedb6e7f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefd0d9c508190b8aedf83f3310513 |
completed | March 9, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b7585bc81909dc2c02e60a55def |
completed | March 14, 2026, 2:06 p.m. |
| NEDg | Description generation | batch_69b56c3a4b708190a55027fd3b2b76e0 |
completed | March 14, 2026, 2:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b56cc5c704819083dac59bf7b3cb83 |
completed | March 14, 2026, 2:12 p.m. |
Created at: March 9, 2026, 3:40 p.m.