Triple
T20493131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuando me enamoro |
E502797
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Martha Julia
Martha Julia is a Mexican actress best known for her roles in telenovelas, often portraying complex or antagonistic characters.
|
E1435143
|
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: Martha Julia | Statement: [Cuando me enamoro, castMember, Martha Julia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martha Julia Context triple: [Cuando me enamoro, castMember, Martha Julia]
-
A.
Martha Hudson
Martha Hudson is an American sprinter who was one of the top female track athletes of her era, notably competing internationally under coach Ed Temple at Tennessee State University.
-
B.
Martha Dix
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
C.
Martha Huggins
Martha Huggins is an actress best known for her role in the classic film "The Ghost and Mrs. Muir."
-
D.
Martha Hunt
Martha Hunt is an American fashion model best known for her work with Victoria’s Secret, including serving as a Victoria’s Secret Angel.
-
E.
Mathilda May
Mathilda May is a French actress and former ballerina best known internationally for her role in the 1985 science fiction horror film "Lifeforce."
- 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: Martha Julia Triple: [Cuando me enamoro, castMember, Martha Julia]
Generated description
Martha Julia is a Mexican actress best known for her roles in telenovelas, often portraying complex or antagonistic characters.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martha Julia Target entity description: Martha Julia is a Mexican actress best known for her roles in telenovelas, often portraying complex or antagonistic characters.
-
A.
Martha Hudson
Martha Hudson is an American sprinter who was one of the top female track athletes of her era, notably competing internationally under coach Ed Temple at Tennessee State University.
-
B.
Martha Dix
Martha Dix was the wife and frequent model of German painter Otto Dix, known from many of his portraits and family scenes.
-
C.
Martha Huggins
Martha Huggins is an actress best known for her role in the classic film "The Ghost and Mrs. Muir."
-
D.
Martha Hunt
Martha Hunt is an American fashion model best known for her work with Victoria’s Secret, including serving as a Victoria’s Secret Angel.
-
E.
Mathilda May
Mathilda May is a French actress and former ballerina best known internationally for her role in the 1985 science fiction horror film "Lifeforce."
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbb3bd081909351525208b41bba |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a089d2ff2c081908f7ccc4ef2767d14 |
completed | May 16, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a089dd1abd08190a662efd4a23eacba |
completed | May 16, 2026, 4:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a089e76035c8190b1b48d102f710fdd |
completed | May 16, 2026, 4:42 p.m. |
Created at: April 16, 2026, 11:35 a.m.