Triple
T5836441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belize City Municipal Airport |
E129482
|
entity |
| Predicate | IATA code |
P2569
|
FINISHED |
| Object |
TZA
TZA is the IATA airport code for Belize City Municipal Airport, a domestic airport serving Belize City in Belize.
|
E551931
|
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: TZA | Statement: [Belize City Municipal Airport, IATA code, TZA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TZA Context triple: [Belize City Municipal Airport, IATA code, TZA]
-
A.
Zimbabwe
Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
-
B.
Tissi
Tissi is a small municipality in the Sardinia region of Italy, located in the province of Sassari.
-
C.
Tanzania
Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
-
D.
Kwaluseni
Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
-
E.
Tamajeq
Tamajeq is a Berber (Amazigh) language spoken primarily by the Tuareg people of the Sahara and Sahel regions.
- 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: TZA Triple: [Belize City Municipal Airport, IATA code, TZA]
Generated description
TZA is the IATA airport code for Belize City Municipal Airport, a domestic airport serving Belize City in Belize.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TZA Target entity description: TZA is the IATA airport code for Belize City Municipal Airport, a domestic airport serving Belize City in Belize.
-
A.
Zimbabwe
Zimbabwe is a landlocked country in southern Africa known for its dramatic landscapes, diverse wildlife, and historical sites such as Victoria Falls and the Great Zimbabwe ruins.
-
B.
Tissi
Tissi is a small municipality in the Sardinia region of Italy, located in the province of Sassari.
-
C.
Tanzania
Tanzania is an East African nation known for its vast wilderness areas, including the Serengeti National Park and Mount Kilimanjaro, as well as its rich cultural diversity.
-
D.
Kwaluseni
Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
-
E.
Tamajeq
Tamajeq is a Berber (Amazigh) language spoken primarily by the Tuareg people of the Sahara and Sahel regions.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034a358708190bfce78e7bd75db36 |
completed | March 22, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a19a6554819086cdae499f4d2247 |
completed | March 23, 2026, 2:12 a.m. |
| NEDg | Description generation | batch_69c0a5ce005c8190a7da8d337caa089c |
completed | March 23, 2026, 2:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0a62cadf481909007a2a16cd36dbf |
completed | March 23, 2026, 2:32 a.m. |
Created at: March 22, 2026, 3:54 p.m.