Triple
T11090955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ana Ofelia Murguía |
E262250
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
El bulto
El bulto is a Mexican film best known for featuring acclaimed actress Ana Ofelia Murguía in a prominent role.
|
E904194
|
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: El bulto | Statement: [Ana Ofelia Murguía, notableWork, El bulto]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El bulto Context triple: [Ana Ofelia Murguía, notableWork, El bulto]
-
A.
Unternehmen Paukenschlag
Unternehmen Paukenschlag was the German World War II U-boat campaign against Allied shipping off the east coast of North America in early 1942, intended to disrupt transatlantic supply lines.
-
B.
The Blow
The Blow is an American indie pop band known for its minimalist electronic sound and introspective, narrative-driven lyrics.
-
C.
The Blue Monster
The Blue Monster is a famously challenging golf course known for its long layout, water hazards, and prominent role in professional tournaments.
-
D.
Las Bombas
Las Bombas is a Metrobús station in Mexico City that serves as a terminus on Line 5 of the bus rapid transit system.
-
E.
El Bombillo
El Bombillo is the popular nickname of Ecuadorian football club Club Sport Emelec, one of the country's most successful and historic teams.
- 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: El bulto Triple: [Ana Ofelia Murguía, notableWork, El bulto]
Generated description
El bulto is a Mexican film best known for featuring acclaimed actress Ana Ofelia Murguía in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: El bulto Target entity description: El bulto is a Mexican film best known for featuring acclaimed actress Ana Ofelia Murguía in a prominent role.
-
A.
Unternehmen Paukenschlag
Unternehmen Paukenschlag was the German World War II U-boat campaign against Allied shipping off the east coast of North America in early 1942, intended to disrupt transatlantic supply lines.
-
B.
The Blow
The Blow is an American indie pop band known for its minimalist electronic sound and introspective, narrative-driven lyrics.
-
C.
The Blue Monster
The Blue Monster is a famously challenging golf course known for its long layout, water hazards, and prominent role in professional tournaments.
-
D.
Las Bombas
Las Bombas is a Metrobús station in Mexico City that serves as a terminus on Line 5 of the bus rapid transit system.
-
E.
El Bombillo
El Bombillo is the popular nickname of Ecuadorian football club Club Sport Emelec, one of the country's most successful and historic teams.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ebae8c8190987b474adb7ede47 |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7c586808190a576803b7406a49e |
completed | April 18, 2026, 8:21 p.m. |
| NEDg | Description generation | batch_69e3f2cafc008190a3504999297f1e4e |
completed | April 18, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3f488819081908f9a4225279cde6b |
completed | April 18, 2026, 9:15 p.m. |
Created at: April 8, 2026, 9:27 p.m.