Triple
T10380877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pepita Embil |
E244636
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Echániz
Echániz is a Spanish surname associated with the family of renowned Basque soprano Pepita Embil.
|
E859474
|
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: Echániz | Statement: [Pepita Embil, familyName, Echániz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Echániz Context triple: [Pepita Embil, familyName, Echániz]
-
A.
Machín
Machín is a stratovolcano in Colombia’s Central Andes known for its explosive eruptions and significant volcanic hazards.
-
B.
Echenique
Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
-
C.
Chaloub
Chaloub is a surname of likely Arabic origin, used as a transliteration variant of the name Chalhub.
-
D.
Guisa
Guisa is a municipality and town located in Cuba’s eastern Granma Province, known for its rural character and historical significance in the Cuban Revolution.
-
E.
Machin
Machin is a surname most notably associated with British sculptor and coin designer Arnold Machin, whose portrait of Queen Elizabeth II appeared on UK coins for decades.
- 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: Echániz Triple: [Pepita Embil, familyName, Echániz]
Generated description
Echániz is a Spanish surname associated with the family of renowned Basque soprano Pepita Embil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Echániz Target entity description: Echániz is a Spanish surname associated with the family of renowned Basque soprano Pepita Embil.
-
A.
Machín
Machín is a stratovolcano in Colombia’s Central Andes known for its explosive eruptions and significant volcanic hazards.
-
B.
Echenique
Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
-
C.
Chaloub
Chaloub is a surname of likely Arabic origin, used as a transliteration variant of the name Chalhub.
-
D.
Guisa
Guisa is a municipality and town located in Cuba’s eastern Granma Province, known for its rural character and historical significance in the Cuban Revolution.
-
E.
Machin
Machin is a surname most notably associated with British sculptor and coin designer Arnold Machin, whose portrait of Queen Elizabeth II appeared on UK coins for decades.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9921fa48190a874aa9a9e385b97 |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7958803e88190a7bbeda4f2c6f32c |
completed | April 9, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69d79784baa481909e57adda27578cc2 |
completed | April 9, 2026, 12:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d7989f8dfc8190b1fe4429f7bb0283 |
completed | April 9, 2026, 12:16 p.m. |
Created at: April 6, 2026, 12:03 p.m.