Triple
T11229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew |
E228
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Andrés
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
|
E2780
|
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: Andrés | Statement: [Andrew, hasVariant, Andrés]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrés Context triple: [Andrew, hasVariant, Andrés]
-
A.
Edwin
Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
-
B.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
-
C.
Gabriel Boric
Gabriel Boric is a Chilean politician and former student leader who became one of the youngest presidents in Chile’s history, known for his left-wing, progressive agenda.
-
D.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
E.
Kato Svanidze
Kato Svanidze was the first wife of Joseph Stalin, remembered primarily for her early death and its profound emotional impact on him.
- 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: Andrés Triple: [Andrew, hasVariant, Andrés]
Generated description
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Andrés Target entity description: Andrés is a Spanish given name commonly used as the equivalent of Andrew.
-
A.
Edwin
Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
-
B.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
-
C.
Gabriel Boric
Gabriel Boric is a Chilean politician and former student leader who became one of the youngest presidents in Chile’s history, known for his left-wing, progressive agenda.
-
D.
Herbert
Herbert is a masculine given name of Germanic origin that has been borne by various notable figures, including U.S. President Herbert Hoover.
-
E.
Guillermo Navarro
Guillermo Navarro is an acclaimed Mexican cinematographer known for his visually striking work on films such as "Pan’s Labyrinth," "Pacific Rim," and collaborations with directors like Guillermo del Toro.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a23ff415ec819082ba80ed3859b71e |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a24e54be7481909db32fd9b1e90cca |
completed | Feb. 28, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69a250b213c881909381abc66f5ebe68 |
completed | Feb. 28, 2026, 2:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2515b915c8190b122de0025bd954f |
completed | Feb. 28, 2026, 2:22 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.