Triple
T16756507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan FA Shield |
E407219
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Jordan |
E237971
|
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: Jordan | Statement: [Jordan FA Shield, location, Jordan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jordan Context triple: [Jordan FA Shield, location, Jordan]
-
A.
Jordan
Jordan is a scientist known for formally describing the bacterial genus Bradyrhizobium.
-
B.
Jordan
"Jordan" is a song featured on Emmylou Harris's bluegrass-influenced album "Roses in the Snow."
-
C.
Jordan
Jordan is a popular Nike-owned athletic footwear and apparel brand originally inspired by basketball legend Michael Jordan and known for its iconic Air Jordan sneakers.
-
D.
Jordan
chosen
Jordan is a municipality in the Philippines that serves as the capital of the island province of Guimaras in the Western Visayas region.
-
E.
Jordan
Jordan was a Formula One racing team and constructor known for launching the careers of several top drivers and competing in the sport during the 1990s and early 2000s.
- 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abe94cc0819099b05cd205d368c5 |
completed | April 18, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52886e48190b7a1e6fccd9a5709 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.