Triple
T14292437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidónio Pais |
E354348
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Sidónio
Sidónio is the given name of Sidónio Pais, a Portuguese military officer, diplomat, and politician who briefly served as President of Portugal during the First Republic.
|
E1092336
|
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: Sidónio | Statement: [Sidónio Pais, givenName, Sidónio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sidónio Context triple: [Sidónio Pais, givenName, Sidónio]
-
A.
Celso
Celso is a small village in southern Italy that serves as a frazione (hamlet) of the municipality of Pollica in the Campania region.
-
B.
Alpidio
Alpidio is a masculine given name of Latin origin, used primarily in Spanish-speaking countries.
-
C.
Nicanor
Nicanor is an ancient Greek scholar known for his critical and exegetical work on Homeric poetry, particularly the Iliad.
-
D.
Nicanor
Nicanor was a Seleucid military commander known for leading royal forces against the Jewish rebels during the Maccabean Revolt in the 2nd century BCE.
-
E.
Clodoaldo
Clodoaldo is a former Brazilian midfielder best known for his role in Brazil’s 1970 World Cup–winning team and his successful career with Santos FC.
- 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: Sidónio Triple: [Sidónio Pais, givenName, Sidónio]
Generated description
Sidónio is the given name of Sidónio Pais, a Portuguese military officer, diplomat, and politician who briefly served as President of Portugal during the First Republic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sidónio Target entity description: Sidónio is the given name of Sidónio Pais, a Portuguese military officer, diplomat, and politician who briefly served as President of Portugal during the First Republic.
-
A.
Celso
Celso is a small village in southern Italy that serves as a frazione (hamlet) of the municipality of Pollica in the Campania region.
-
B.
Alpidio
Alpidio is a masculine given name of Latin origin, used primarily in Spanish-speaking countries.
-
C.
Nicanor
Nicanor is an ancient Greek scholar known for his critical and exegetical work on Homeric poetry, particularly the Iliad.
-
D.
Nicanor
Nicanor was a Seleucid military commander known for leading royal forces against the Jewish rebels during the Maccabean Revolt in the 2nd century BCE.
-
E.
Clodoaldo
Clodoaldo is a former Brazilian midfielder best known for his role in Brazil’s 1970 World Cup–winning team and his successful career with Santos FC.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de7179368081908117a9ccfbf94fd4 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1fee448190bcafb37dd6618d60 |
completed | May 8, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69fd3e5f333c8190bdce30a813bea59e |
completed | May 8, 2026, 1:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3ed1fe288190b83dc432b61f0b4f |
completed | May 8, 2026, 1:39 a.m. |
Created at: April 10, 2026, 1:11 a.m.