Triple
T11835581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHANNEX |
E281506
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Channel Express |
E58611
|
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: Channel Express | Statement: [CHANNEX, usedBy, Channel Express]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Channel Express Context triple: [CHANNEX, usedBy, Channel Express]
-
A.
Channel Express
chosen
Channel Express was a British airline that operated cargo and passenger services before rebranding and evolving into the low-cost carrier Jet2.com.
-
B.
TNT Express
TNT Express is an international courier and logistics company known for its global parcel delivery and express mail services.
-
C.
National Express
National Express is a major UK-based coach and bus operator providing long-distance and local passenger transport services domestically and internationally.
-
D.
UP Express
UP Express is a dedicated airport rail link in Toronto that provides fast, frequent train service between Union Station downtown and Toronto Pearson International Airport.
-
E.
DHL
DHL is the Dag Hammarskjöld Library, the United Nations’ main research and information resource center located at its headquarters in New York.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62fec0881908c7b89c0b5bcc9a2 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f28131f75c8190b379e65d5a258e7b |
completed | April 29, 2026, 10:07 p.m. |
Created at: April 8, 2026, 9:43 p.m.