Triple
T21630023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BP Top 8 |
E533804
|
entity |
| Predicate | successorCompetition |
P13377
|
FINISHED |
| Object | MTN 8 |
—
|
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: MTN 8 | Statement: [BP Top 8, successorCompetition, MTN 8]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MTN 8 Context triple: [BP Top 8, successorCompetition, MTN 8]
-
A.
MTN 8
chosen
MTN 8 is a South African top-flight football knockout cup competition contested by the eight highest-placed teams from the previous Premier Soccer League season.
-
B.
MTN8
MTN8 is a South African knockout football (soccer) cup competition contested by the top eight teams from the Premier Soccer League.
-
C.
MTN
MTN is the IATA airport code for Martin State Airport, a public airport serving the Baltimore, Maryland area.
-
D.
MTN
MTN is the stock ticker symbol for Vail Resorts, a major operator of ski resorts and mountain recreation properties.
-
E.
MTA Africa
MTA Africa is the African regional television channel of the global Islamic network MTA International, broadcasting religious and educational content across the African continent.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5215ae3c81909e6dedba23822970 |
completed | April 27, 2026, 12:09 p.m. |
Created at: April 16, 2026, 6:34 p.m.