Triple
T18352185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cano |
E439691
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Elena Cano
Elena Cano is a notable individual recognized for achievements associated with the surname Cano.
|
E1319234
|
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: Elena Cano | Statement: [Cano, hasNotableBearer, Elena Cano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elena Cano Context triple: [Cano, hasNotableBearer, Elena Cano]
-
A.
Ifigenia Martínez
Ifigenia Martínez is a Mexican economist, diplomat, and left-wing politician best known as one of the founding figures of modern progressive politics in Mexico.
-
B.
María José Martínez
María José Martínez is a film producer known for her work on the documentary "Maradona by Kusturica."
-
C.
Maria Navarro
Maria Navarro is a personal name that may refer to various individuals, including professionals, artists, or public figures, depending on context.
-
D.
Marian Álvarez
Marian Álvarez is a Spanish film and television actress known for her intense dramatic roles and critically acclaimed performances.
-
E.
María Isabel Nadal
María Isabel Nadal is the younger sister of Spanish tennis champion Rafael Nadal, known for maintaining a relatively private life despite her brother’s global fame.
- 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: Elena Cano Triple: [Cano, hasNotableBearer, Elena Cano]
Generated description
Elena Cano is a notable individual recognized for achievements associated with the surname Cano.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elena Cano Target entity description: Elena Cano is a notable individual recognized for achievements associated with the surname Cano.
-
A.
Ifigenia Martínez
Ifigenia Martínez is a Mexican economist, diplomat, and left-wing politician best known as one of the founding figures of modern progressive politics in Mexico.
-
B.
María José Martínez
María José Martínez is a film producer known for her work on the documentary "Maradona by Kusturica."
-
C.
Maria Navarro
Maria Navarro is a personal name that may refer to various individuals, including professionals, artists, or public figures, depending on context.
-
D.
Marian Álvarez
Marian Álvarez is a Spanish film and television actress known for her intense dramatic roles and critically acclaimed performances.
-
E.
María Isabel Nadal
María Isabel Nadal is the younger sister of Spanish tennis champion Rafael Nadal, known for maintaining a relatively private life despite her brother’s global fame.
- 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_69d8b918221c8190a9f7b563d64ac677 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f8f07c8190a1506d4a327369d0 |
completed | April 19, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03cc2b4b3c81909ff81c7861e0ddba |
completed | May 13, 2026, 12:56 a.m. |
| NEDg | Description generation | batch_6a03ccd2c23881909c200be266dab873 |
completed | May 13, 2026, 12:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03cd535cf08190a5dfc9118be68e17 |
completed | May 13, 2026, 1:01 a.m. |
Created at: April 10, 2026, 10:37 a.m.