Triple
T137616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrés |
E2780
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
André
André is a given name of French origin commonly used in various languages as a form of "Andrew."
|
E24111
|
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: André | Statement: [Andrés, hasVariant, André]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: André Context triple: [Andrés, hasVariant, André]
-
A.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
D.
Stephen Sauvestre
Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
-
E.
René Thomas
René Thomas was a Belgian biophysicist and geneticist known for pioneering work in the logical modeling of gene regulatory networks and dynamical systems in biology.
- 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: André Triple: [Andrés, hasVariant, André]
Generated description
André is a given name of French origin commonly used in various languages as a form of "Andrew."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: André Target entity description: André is a given name of French origin commonly used in various languages as a form of "Andrew."
-
A.
Jacques
Jacques is the French form of the given name James, commonly used in French-speaking countries.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Georges
Georges is a masculine given name of Greek origin, commonly used in French-speaking countries and derived from the name George, meaning "farmer" or "earthworker."
-
D.
Stephen Sauvestre
Stephen Sauvestre was a French architect best known for designing the architectural embellishments and final aesthetic of the Eiffel Tower.
-
E.
René Thomas
René Thomas was a Belgian biophysicist and geneticist known for pioneering work in the logical modeling of gene regulatory networks and dynamical systems in biology.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a6cab88190944c8f74d8d1605c |
completed | Feb. 28, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a305e1600c81909e421bf423229878 |
completed | Feb. 28, 2026, 3:12 p.m. |
| NEDg | Description generation | batch_69a306a68d688190a65a22accab1085b |
completed | Feb. 28, 2026, 3:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a306fb004881908a23a86ab1cf1fc6 |
completed | Feb. 28, 2026, 3:17 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.