Triple
T217018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broad Front (Chile) |
E4127
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
FA
FA is a Chilean left-wing political coalition known for uniting various progressive parties and movements to challenge the country’s traditional political blocs.
|
E27823
|
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: FA | Statement: [Broad Front (Chile), shortName, FA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FA Context triple: [Broad Front (Chile), shortName, FA]
-
A.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
-
B.
SF
SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
-
C.
Flo
Flo was one of Jane Goodall’s most famous Gombe chimpanzees, known as a highly influential matriarch whose life and family were central to long-term studies of chimpanzee behavior and social structure.
-
D.
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
-
E.
FFF
FFF is a global youth-led climate movement advocating for urgent action against climate change through school strikes and public demonstrations.
- 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: FA Triple: [Broad Front (Chile), shortName, FA]
Generated description
FA is a Chilean left-wing political coalition known for uniting various progressive parties and movements to challenge the country’s traditional political blocs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FA Target entity description: FA is a Chilean left-wing political coalition known for uniting various progressive parties and movements to challenge the country’s traditional political blocs.
-
A.
F
F is the New York Stock Exchange ticker symbol for Ford Motor Company, the American multinational automaker known for mass-producing automobiles and pioneering assembly line manufacturing.
-
B.
SF
SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
-
C.
Flo
Flo was one of Jane Goodall’s most famous Gombe chimpanzees, known as a highly influential matriarch whose life and family were central to long-term studies of chimpanzee behavior and social structure.
-
D.
FÜ
FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
-
E.
FFF
FFF is a global youth-led climate movement advocating for urgent action against climate change through school strikes and public demonstrations.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c4edfa081909fe97c86c3c7801d |
completed | Feb. 28, 2026, 3:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3441e48b48190849c7bff04134ac9 |
completed | Feb. 28, 2026, 7:38 p.m. |
| NEDg | Description generation | batch_69a344ba0a4c8190986d490f502cb6ab |
completed | Feb. 28, 2026, 7:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a34520805481909c4f1ea05262665b |
completed | Feb. 28, 2026, 7:42 p.m. |
Created at: Feb. 28, 2026, 2:53 a.m.