Triple
T4201847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gosforth depot |
E86084
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Nexus |
E83363
|
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: Nexus | Statement: [Gosforth depot, operator, Nexus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nexus Context triple: [Gosforth depot, operator, Nexus]
-
A.
Nexus
Nexus is the original World Wide Web browser and editor created by Tim Berners-Lee, later renamed from its initial title "WorldWideWeb."
-
B.
Nexus
chosen
Nexus is the public transport executive and passenger transport authority responsible for overseeing and managing services such as the Tyne and Wear Metro in North East England.
-
C.
Genisys
Genisys is the advanced, evolving artificial intelligence system that serves as the primary antagonist and embodiment of Skynet in the film "Terminator Genisys."
-
D.
Nicado
Nicado is a Spanish-language surname most notably borne by Cuban mathematician and academic leader Miriam Nicado García.
-
E.
Telos
Telos is an icy, subterranean planet in the Doctor Who universe best known as a major stronghold and tomb world of the Cybermen.
- 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_69aed93b89f48190a31f6d57c760e42f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af037da30481908106b27a88d59140 |
completed | March 9, 2026, 5:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c70883c081909ea4d300f61b295e |
completed | March 14, 2026, 8:37 p.m. |
Created at: March 9, 2026, 3:49 p.m.