Triple
T928851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José de San Martín |
E20046
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
Yapeyú
Yapeyú is a small town in northeastern Argentina, historically notable as the birthplace of independence leader José de San Martín.
|
E112009
|
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: Yapeyú | Statement: [José de San Martín, birthPlace, Yapeyú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yapeyú Context triple: [José de San Martín, birthPlace, Yapeyú]
-
A.
Panguipulli
Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
-
B.
Cajicá
Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
-
C.
Tocancipá
Tocancipá is a Colombian municipality in the department of Cundinamarca, known for its industrial activity, motorsport circuit, and proximity to Bogotá.
-
D.
Villapinzón
Villapinzón is a Colombian town and municipality in the department of Cundinamarca, known for its leather industry and location in the Andean highlands.
-
E.
Tarija
Tarija is a city in southern Bolivia known for its colonial architecture, mild climate, and surrounding wine-producing valleys.
- 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: Yapeyú Triple: [José de San Martín, birthPlace, Yapeyú]
Generated description
Yapeyú is a small town in northeastern Argentina, historically notable as the birthplace of independence leader José de San Martín.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yapeyú Target entity description: Yapeyú is a small town in northeastern Argentina, historically notable as the birthplace of independence leader José de San Martín.
-
A.
Panguipulli
Panguipulli is a scenic town in southern Chile known for its lakeside setting, surrounding volcanoes, and role as a gateway to the Andean lake district.
-
B.
Cajicá
Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
-
C.
Tocancipá
Tocancipá is a Colombian municipality in the department of Cundinamarca, known for its industrial activity, motorsport circuit, and proximity to Bogotá.
-
D.
Villapinzón
Villapinzón is a Colombian town and municipality in the department of Cundinamarca, known for its leather industry and location in the Andean highlands.
-
E.
Tarija
Tarija is a city in southern Bolivia known for its colonial architecture, mild climate, and surrounding wine-producing valleys.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b34775ac8190aabbd047a36cec6b |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a933a103908190a624039492079f82 |
completed | March 5, 2026, 7:41 a.m. |
| NEDg | Description generation | batch_69a94d60cb3c81908dc3af7bc395505f |
completed | March 5, 2026, 9:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a963c897888190bec5decc6010c9d6 |
completed | March 5, 2026, 11:06 a.m. |
Created at: March 1, 2026, 7:40 p.m.