Triple
T15479156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bank of Guatemala |
E376867
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
Banguat
Banguat is the central bank of Guatemala, responsible for the country’s monetary policy, currency issuance, and financial stability.
|
E1159715
|
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: Banguat | Statement: [Bank of Guatemala, abbreviation, Banguat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Banguat Context triple: [Bank of Guatemala, abbreviation, Banguat]
-
A.
Bangu
Bangu is a working-class neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its hot climate, historic textile industry, and the Bangu Atlético Clube football team.
-
B.
Nabaruh
Nabaruh is a city located in Egypt’s Dakahlia Governorate in the Nile Delta region.
-
C.
Baatonun
Baatonun is a Gur language spoken primarily by the Bariba (Baatombu) people in parts of Benin and neighboring West African regions.
-
D.
Bato
Bato is a coastal municipality on the island province of Catanduanes in the Bicol Region of the Philippines, known for its rural landscapes and proximity to the Pacific Ocean.
-
E.
Batabanó
Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
- 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: Banguat Triple: [Bank of Guatemala, abbreviation, Banguat]
Generated description
Banguat is the central bank of Guatemala, responsible for the country’s monetary policy, currency issuance, and financial stability.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Banguat Target entity description: Banguat is the central bank of Guatemala, responsible for the country’s monetary policy, currency issuance, and financial stability.
-
A.
Bangu
Bangu is a working-class neighborhood in the West Zone of Rio de Janeiro, Brazil, known for its hot climate, historic textile industry, and the Bangu Atlético Clube football team.
-
B.
Nabaruh
Nabaruh is a city located in Egypt’s Dakahlia Governorate in the Nile Delta region.
-
C.
Baatonun
Baatonun is a Gur language spoken primarily by the Bariba (Baatombu) people in parts of Benin and neighboring West African regions.
-
D.
Bato
Bato is a coastal municipality on the island province of Catanduanes in the Bicol Region of the Philippines, known for its rural landscapes and proximity to the Pacific Ocean.
-
E.
Batabanó
Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f8a77a081909f12f13660452f4a |
completed | April 16, 2026, 1:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2d0b3e7881908f195701fe222371 |
completed | May 9, 2026, 12:48 p.m. |
| NEDg | Description generation | batch_69ff2e4010dc8190b0f81d03acf8ba41 |
completed | May 9, 2026, 12:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff310c2d5c819093295c45307176ec |
completed | May 9, 2026, 1:05 p.m. |
Created at: April 10, 2026, 3:34 a.m.