Triple
T150235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabriel García Márquez |
E3414
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Mercedes Barcha
Mercedes Barcha was the longtime wife and muse of Nobel Prize–winning author Gabriel García Márquez, known for her steadfast support throughout his literary career.
|
E32064
|
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: Mercedes Barcha | Statement: [Gabriel García Márquez, spouse, Mercedes Barcha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mercedes Barcha Context triple: [Gabriel García Márquez, spouse, Mercedes Barcha]
-
A.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
B.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
C.
Rita
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
-
D.
Barbara Dickson
Barbara Dickson is a Scottish singer and actress known for her folk-inspired pop music and roles in musical theatre, including the hit musical "Blood Brothers."
-
E.
Dominique Horwitz
Dominique Horwitz is a German-French actor and singer known for his roles in European cinema and television, particularly in war and historical dramas.
- 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: Mercedes Barcha Triple: [Gabriel García Márquez, spouse, Mercedes Barcha]
Generated description
Mercedes Barcha was the longtime wife and muse of Nobel Prize–winning author Gabriel García Márquez, known for her steadfast support throughout his literary career.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mercedes Barcha Target entity description: Mercedes Barcha was the longtime wife and muse of Nobel Prize–winning author Gabriel García Márquez, known for her steadfast support throughout his literary career.
-
A.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
B.
Estelle
Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
-
C.
Rita
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
-
D.
Barbara Dickson
Barbara Dickson is a Scottish singer and actress known for her folk-inspired pop music and roles in musical theatre, including the hit musical "Blood Brothers."
-
E.
Dominique Horwitz
Dominique Horwitz is a German-French actor and singer known for his roles in European cinema and television, particularly in war and historical dramas.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3736b2ff081909a5b36a93fa16130 |
completed | Feb. 28, 2026, 10:59 p.m. |
| NEDg | Description generation | batch_69a3741398148190b33de6d93ccc0725 |
completed | Feb. 28, 2026, 11:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3746ba85c8190bd45c2a5717317dc |
completed | Feb. 28, 2026, 11:04 p.m. |
Created at: Feb. 28, 2026, 2:31 a.m.