Triple
T6002309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badalona |
E133624
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
FINISHED |
| Object |
Tiana
Tiana is a small municipality in Catalonia, Spain, located near the coastal city of Barcelona.
|
E562511
|
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: Tiana | Statement: [Badalona, neighboringMunicipality, Tiana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiana Context triple: [Badalona, neighboringMunicipality, Tiana]
-
A.
Tiana
Tiana is a Disney Princess known for her hardworking, ambitious nature and role as the first African-American princess in Disney’s animated film "The Princess and the Frog."
-
B.
Dorinda
Dorinda is a feminine given name, often considered a variant or elaboration of Dorothy, used in various English-speaking cultures.
-
C.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
D.
Rosalina
Rosalina is a celestial princess and guardian of the cosmos in Nintendo's Super Mario series, known for caring for the star-like Lumas and piloting the Comet Observatory.
-
E.
Alicia
Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
- 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: Tiana Triple: [Badalona, neighboringMunicipality, Tiana]
Generated description
Tiana is a small municipality in Catalonia, Spain, located near the coastal city of Barcelona.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiana Target entity description: Tiana is a small municipality in Catalonia, Spain, located near the coastal city of Barcelona.
-
A.
Tiana
Tiana is a Disney Princess known for her hardworking, ambitious nature and role as the first African-American princess in Disney’s animated film "The Princess and the Frog."
-
B.
Dorinda
Dorinda is a feminine given name, often considered a variant or elaboration of Dorothy, used in various English-speaking cultures.
-
C.
Marzelline
Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
-
D.
Rosalina
Rosalina is a celestial princess and guardian of the cosmos in Nintendo's Super Mario series, known for caring for the star-like Lumas and piloting the Comet Observatory.
-
E.
Alicia
Alicia is the given name of the American singer, songwriter, and pianist Alicia Keys, known for her soulful R&B music and powerful vocals.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee9cb0c8190a3361c36ac3944af |
completed | March 22, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c10888e58c8190a9454de046b27faf |
completed | March 23, 2026, 9:31 a.m. |
| NEDg | Description generation | batch_69c10b5816548190b73f19e12cdf8e03 |
completed | March 23, 2026, 9:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c10c39fb848190a557278d3cd23560 |
completed | March 23, 2026, 9:47 a.m. |
Created at: March 22, 2026, 4:05 p.m.