Triple
T8233209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuartel General de las FAMET |
E192342
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | FAMET |
E192338
|
NE FINISHED |
How this triple was built (2 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: FAMET | Statement: [Cuartel General de las FAMET, partOf, FAMET]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FAMET Context triple: [Cuartel General de las FAMET, partOf, FAMET]
-
A.
FAMET
chosen
FAMET is the Spanish Army’s aviation branch responsible for operating and supporting its helicopter and air mobility units.
-
B.
FAMO
FAMO was a German vehicle manufacturer best known for producing military half-tracks and armored vehicles for the Wehrmacht during World War II.
-
C.
FAM
FAM is the national governing body responsible for overseeing and developing football in Malaysia.
-
D.
FAM
FAM is the acronym commonly used to refer to the Mexican Air Force, the aerial warfare branch of Mexico’s armed forces.
-
E.
FAMa
FAMa is the national military force of Mali responsible for the country’s defense and security operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82db5b90819085d1ad7c2e27bfcc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb782658fc8190885dc267355ff245 |
completed | March 31, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd67f7dcec81909b74fd2da3609fc3 |
completed | April 1, 2026, 6:46 p.m. |
Created at: March 30, 2026, 5:46 p.m.