Triple
T6929042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angolan Air Force |
E160386
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
FANA
FANA is the acronym for the Angolan Air Force, the aerial warfare branch of Angola’s armed forces.
|
E628879
|
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: FANA | Statement: [Angolan Air Force, abbreviation, FANA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FANA Context triple: [Angolan Air Force, abbreviation, FANA]
-
A.
Fanari
Fanari is the former name of Mikrolimano, a picturesque small harbor and popular dining and nightlife spot in Piraeus, Greece.
-
B.
FAN-nee
FAN-nee is the stress pattern indicating that the primary emphasis falls on the first syllable of the name “Fannie.”
-
C.
Fumei
Fumei is a given name most notably borne by Mao Fumei, the first wife of Chinese leader Chiang Kai-shek.
-
D.
Franchesca
Franchesca is a feminine given name, typically considered a variant spelling of Francesca and used in various English-speaking and European cultures.
-
E.
Fang
Fang is a Bantu language widely spoken by the Fang people of Central Africa, particularly in Equatorial Guinea, Gabon, and Cameroon.
- 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: FANA Triple: [Angolan Air Force, abbreviation, FANA]
Generated description
FANA is the acronym for the Angolan Air Force, the aerial warfare branch of Angola’s armed forces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FANA Target entity description: FANA is the acronym for the Angolan Air Force, the aerial warfare branch of Angola’s armed forces.
-
A.
Fanari
Fanari is the former name of Mikrolimano, a picturesque small harbor and popular dining and nightlife spot in Piraeus, Greece.
-
B.
FAN-nee
FAN-nee is the stress pattern indicating that the primary emphasis falls on the first syllable of the name “Fannie.”
-
C.
Fumei
Fumei is a given name most notably borne by Mao Fumei, the first wife of Chinese leader Chiang Kai-shek.
-
D.
Franchesca
Franchesca is a feminine given name, typically considered a variant spelling of Francesca and used in various English-speaking and European cultures.
-
E.
Fang
Fang is a Bantu language widely spoken by the Fang people of Central Africa, particularly in Equatorial Guinea, Gabon, and Cameroon.
- 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_69c6884e15208190b9e91487eaafcf85 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da1de28881908579bc198e74203e |
completed | March 27, 2026, 7:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7514774d88190af212d7953014703 |
completed | March 28, 2026, 3:55 a.m. |
| NEDg | Description generation | batch_69c7524d677c81909531ba9bb46f2632 |
completed | March 28, 2026, 4 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c752bef2808190843f3cad53aa5702 |
completed | March 28, 2026, 4:02 a.m. |
Created at: March 27, 2026, 2:27 p.m.