Triple
T10321068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Moroccan Football Federation |
E242137
|
entity |
| Predicate | affiliation |
P10
|
FINISHED |
| Object | UNAF |
E570969
|
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: UNAF | Statement: [Royal Moroccan Football Federation, affiliation, UNAF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UNAF Context triple: [Royal Moroccan Football Federation, affiliation, UNAF]
-
A.
UNAF
chosen
UNAF (Union of North African Football Federations) is the regional governing body that organizes and oversees football activities and competitions among North African national associations.
-
B.
UNCAF
UNCAF is the Central American Football Union, the regional governing body for association football in Central America under CONCACAF.
-
C.
UNDAF
UNDAF is the strategic planning framework that guides how United Nations agencies coordinate their development assistance in a given country.
-
D.
UNA
UNA is the stock ticker symbol for Unilever, a major multinational consumer goods company known for its wide range of food, personal care, and household products.
-
E.
UNA
UNA is a public university located in Florence, Alabama, known for its regional academic programs and historic campus.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d6cbbb548190b757ec5a02d60e5c |
completed | April 7, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d9b2ad881909f3076f8f9d1b1d3 |
completed | April 9, 2026, 3:31 a.m. |
Created at: April 6, 2026, 11:50 a.m.