Triple
T12771287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Kowloon Reclamation |
E305251
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Jordan |
E851031
|
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: [West Kowloon Reclamation, adjacentTo, Jordan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jordan Context triple: [West Kowloon Reclamation, adjacentTo, 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
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.
-
E.
Jordan
chosen
Jordan is a small community in the town of Lincoln, Ontario, known for its wineries, fruit farms, and scenic location on the Niagara Peninsula.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df4b36c81909bcc913dd5e535f8 |
completed | April 10, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684f9ba848190b680d730b6a3b972 |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:28 p.m.