Triple
T3123493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dudelange |
E65239
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Dan Biancalana
Dan Biancalana is a Luxembourgish politician who serves as the mayor of the city of Dudelange.
|
E328666
|
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: Dan Biancalana | Statement: [Dudelange, hasMayor, Dan Biancalana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Biancalana Context triple: [Dudelange, hasMayor, Dan Biancalana]
-
A.
Brian Bilello
Brian Bilello is an American soccer executive best known for leading Major League Soccer’s New England Revolution as the club’s president.
-
B.
Gene Ruggiero
Gene Ruggiero was an American film editor best known for his work on classic Hollywood productions, including the musical "Oklahoma!" (1955).
-
C.
Al DeRogatis
Al DeRogatis was an American football player turned prominent television and radio color commentator, known especially for his insightful analysis during major NFL broadcasts.
-
D.
David Matalon
David Matalon is a film producer best known for his work on the acclaimed 1993 drama "What's Eating Gilbert Grape."
-
E.
Anthony Di Ninno
Anthony Di Ninno is a cinematographer best known for his work on the animated feature film "Captain Underpants: The First Epic Movie."
- 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: Dan Biancalana Triple: [Dudelange, hasMayor, Dan Biancalana]
Generated description
Dan Biancalana is a Luxembourgish politician who serves as the mayor of the city of Dudelange.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dan Biancalana Target entity description: Dan Biancalana is a Luxembourgish politician who serves as the mayor of the city of Dudelange.
-
A.
Brian Bilello
Brian Bilello is an American soccer executive best known for leading Major League Soccer’s New England Revolution as the club’s president.
-
B.
Gene Ruggiero
Gene Ruggiero was an American film editor best known for his work on classic Hollywood productions, including the musical "Oklahoma!" (1955).
-
C.
Al DeRogatis
Al DeRogatis was an American football player turned prominent television and radio color commentator, known especially for his insightful analysis during major NFL broadcasts.
-
D.
David Matalon
David Matalon is a film producer best known for his work on the acclaimed 1993 drama "What's Eating Gilbert Grape."
-
E.
Anthony Di Ninno
Anthony Di Ninno is a cinematographer best known for his work on the animated feature film "Captain Underpants: The First Epic Movie."
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52c105c8190b8128e66d9b9e8a0 |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f72c2048190ab2aa40a109f5976 |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b21083db7081908f8bc4240fc2b08b |
completed | March 12, 2026, 1:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b210fa8a7c8190ae4527161aa3af54 |
completed | March 12, 2026, 1:03 a.m. |
Created at: March 8, 2026, 3:04 p.m.