Triple
T4171560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte LYNX Blue Line |
E84574
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | LYNX |
E317550
|
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: LYNX | Statement: [Charlotte LYNX Blue Line, brand, LYNX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LYNX Context triple: [Charlotte LYNX Blue Line, brand, LYNX]
-
A.
LYNX
chosen
LYNX is a public bus transportation system serving the Orlando, Florida metropolitan area.
-
B.
Lynx
Lynx is a high-speed serial computer bus interface standard, better known as IEEE 1394 or FireWire, used for real-time data transfer between digital devices.
-
C.
Lyn
Lyn is a Norwegian football club based in Oslo with a long history in the country’s top divisions.
-
D.
Eurasian lynx
The Eurasian lynx is a medium-sized wild cat native to European and Siberian forests, recognizable by its tufted ears, short tail, and spotted coat, and is one of the continent’s top predators.
-
E.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c9e12c81908d0b22671fea2453 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f51cac88190b6e849181fb78938 |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:45 p.m.