Triple
T22963443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EFA |
E570968
|
entity |
| Predicate | affiliation |
P10
|
FINISHED |
| Object | UAFA |
—
|
NE NERFINISHED |
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: UAFA | Statement: [EFA, affiliation, UAFA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UAFA Context triple: [EFA, affiliation, UAFA]
-
A.
UAFA
chosen
UAFA is the Union of Arab Football Associations, the regional governing body that organizes football competitions among Arab countries in Asia and Africa.
-
B.
USAf
USAf is the commonly used abbreviation for Universities South Africa, the representative body for public universities in South Africa.
-
C.
UFL
UFL is a common abbreviation for the University of Florida, a major public research university in Gainesville known for its strong academics and athletics.
-
D.
UFL
UFL is a military training exercise known as Ulchi Focus Lens, historically conducted by South Korea and the United States to enhance readiness and coordination in defense operations.
-
E.
UFL
UFL is a professional American football league that serves as an alternative spring season competition to the NFL.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f66fbc8190a4a7b73d17537132 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.