Triple
T17053620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peru national under-17 football team |
E413763
|
entity |
| Predicate | governingBodyAbbreviation |
P2886
|
FINISHED |
| Object | FPF |
E1243700
|
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: FPF | Statement: [Peru national under-17 football team, governingBodyAbbreviation, FPF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FPF Context triple: [Peru national under-17 football team, governingBodyAbbreviation, FPF]
-
A.
FPF
chosen
FPF is the Peruvian Football Federation, the main organization responsible for overseeing and regulating football activities in Peru.
-
B.
FPF
FPF is the Portuguese Football Federation, the national governing body responsible for organizing and overseeing football in Portugal, including its national teams.
-
C.
FP
FP is the station code for Floral Park station on the Long Island Rail Road in New York.
-
D.
PFG
PFG is the stock ticker symbol for Principal Financial Group, a U.S.-based global financial services and investment management company.
-
E.
PF
PF is the vehicle registration code used on license plates for the German city of Pforzheim.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa491008190ad013ee37532aa51 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012343eca0819086a07511c5d22878 |
completed | May 11, 2026, 12:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.