Triple
T17100969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor of Lima |
E414978
|
entity |
| Predicate | positionHeldBy |
P8
|
FINISHED |
| Object |
Jorge Muñoz Wells
Jorge Muñoz Wells is a Peruvian lawyer and politician who served as the mayor of Lima, leading the capital city’s municipal government.
|
E1335512
|
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: Jorge Muñoz Wells | Statement: [Mayor of Lima, positionHeldBy, Jorge Muñoz Wells]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jorge Muñoz Wells Context triple: [Mayor of Lima, positionHeldBy, Jorge Muñoz Wells]
-
A.
David Mendoza
David Mendoza was a composer and conductor active in early 20th-century cinema, known for his work on silent film scores.
-
B.
R. Orlando Duenas
R. Orlando Duenas is a film editor best known for his work on the animated feature "The Peanuts Movie."
-
C.
Luis Lopez-Fitzgerald
Luis Lopez-Fitzgerald is a central romantic lead and heroic police officer in the American soap opera "Passions," known for his tumultuous relationships and family drama.
-
D.
Miguel Ángel Menéndez
Miguel Ángel Menéndez is a person notable enough to be recognized as a prominent bearer of the surname Menéndez.
-
E.
Armando Muñiz
Armando Muñiz is a former Mexican-American professional welterweight boxer known for his world title challenges during the 1970s.
- 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: Jorge Muñoz Wells Triple: [Mayor of Lima, positionHeldBy, Jorge Muñoz Wells]
Generated description
Jorge Muñoz Wells is a Peruvian lawyer and politician who served as the mayor of Lima, leading the capital city’s municipal government.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jorge Muñoz Wells Target entity description: Jorge Muñoz Wells is a Peruvian lawyer and politician who served as the mayor of Lima, leading the capital city’s municipal government.
-
A.
David Mendoza
David Mendoza was a composer and conductor active in early 20th-century cinema, known for his work on silent film scores.
-
B.
R. Orlando Duenas
R. Orlando Duenas is a film editor best known for his work on the animated feature "The Peanuts Movie."
-
C.
Luis Lopez-Fitzgerald
Luis Lopez-Fitzgerald is a central romantic lead and heroic police officer in the American soap opera "Passions," known for his tumultuous relationships and family drama.
-
D.
Miguel Ángel Menéndez
Miguel Ángel Menéndez is a person notable enough to be recognized as a prominent bearer of the surname Menéndez.
-
E.
Armando Muñiz
Armando Muñiz is a former Mexican-American professional welterweight boxer known for his world title challenges during the 1970s.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc0182cc8190b8aa9c980f11ba57 |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a051701512c819080be8649f1f1b401 |
completed | May 14, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_6a05184e0cc881909aad820f5afc34be |
completed | May 14, 2026, 12:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05189feab08190ad33ec2f5711fecb |
completed | May 14, 2026, 12:34 a.m. |
Created at: April 10, 2026, 5:35 a.m.