Triple
T20099082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon tramway network |
E496483
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | T4 |
—
|
NE NERFINISHED |
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: T4 | Statement: [Lyon tramway network, hasLine, T4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T4 Context triple: [Lyon tramway network, hasLine, T4]
-
A.
T4
T4 is a light rail/tram line of the Trambesòs network serving the Barcelona metropolitan area.
-
B.
T4
T4 is one of the lines of the Athens tram system, providing urban light-rail service across part of the Athens metropolitan area.
-
C.
T4
chosen
T4 is a tram line serving the city of Villeurbanne as part of the Lyon metropolitan public transport network in France.
-
D.
T4
T4 is the large, modern main passenger terminal at Adolfo Suárez Madrid–Barajas Airport in Madrid, Spain, known for its distinctive architecture and extensive international flight operations.
-
E.
T4
T4 is the fourth passenger terminal at Melbourne Airport, serving as one of the airport’s main facilities for domestic and low-cost airline operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666e306c81909c0ef617e0f6fccf |
completed | April 20, 2026, 5:46 p.m. |
Created at: April 11, 2026, 11:26 p.m.