Triple
T13248536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmers End |
E315467
|
entity |
| Predicate | servedByTramRoute |
P92625
|
FINISHED |
| Object | Tramlink route 4 |
E128281
|
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: Tramlink route 4 | Statement: [Elmers End, servedByTramRoute, Tramlink route 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tramlink route 4 Context triple: [Elmers End, servedByTramRoute, Tramlink route 4]
-
A.
Tram line 4
Tram line 4 is one of Budapest’s busiest urban tram routes, running across the city center and connecting major hubs including Nyugati tér.
-
B.
Tramlink
chosen
Tramlink is a light rail tram system serving the Croydon area and surrounding districts in South London.
-
C.
Tram 17
Tram 17 is a tram line in Geneva’s public transport system operated by the city’s transit authority.
-
D.
Tram line 6
Tram line 6 is one of Budapest’s busiest and most frequent tram routes, running along the Grand Boulevard and serving major hubs such as Nyugati tér.
-
E.
Tram 12
Tram 12 is a major tram line in Geneva’s public transport system, connecting key neighborhoods and suburbs across the city.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f71c5388190a6e122e14384efd7 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff37f7448190b9c555cae010d3b6 |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:24 p.m.