Triple
T11481952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FAES |
E272172
|
entity |
| Predicate | usesAcronym |
P43
|
FINISHED |
| Object | FAES |
E272172
|
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: FAES | Statement: [FAES, usesAcronym, FAES]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FAES Context triple: [FAES, usesAcronym, FAES]
-
A.
FAES
chosen
FAES is the acronym for the Armed Forces of El Salvador, the country's unified military institution responsible for national defense and security.
-
B.
FAE
FAE is the IATA airport code for Vágar Airport, the main international gateway to the Faroe Islands.
-
C.
FAE
FAE is the acronym for the Ecuadorian Air Force, the aerial warfare branch of Ecuador’s military responsible for defending the nation’s airspace.
-
D.
FEAS
FEAS is the Faculty of Engineering and Architectural Science at Toronto Metropolitan University, encompassing programs in engineering, architecture, and related applied sciences.
-
E.
AFESD
AFESD is a regional Arab financial institution that provides development financing and support to promote economic and social progress in Arab countries.
- 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_69d6aae1b09881909ce2ded3fa0c14fa |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d85a1d86b88190b180f6b0d0a27029 |
completed | April 10, 2026, 2:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e604410fbc819098b101c029b63525 |
completed | April 20, 2026, 10:47 a.m. |
Created at: April 8, 2026, 9:36 p.m.