Triple
T22687645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bareilly–Pilibhit–Lalkuan line |
E560959
|
entity |
| Predicate | servesTown |
P847
|
FINISHED |
| Object | Lalkuan |
—
|
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: Lalkuan | Statement: [Bareilly–Pilibhit–Lalkuan line, servesTown, Lalkuan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lalkuan Context triple: [Bareilly–Pilibhit–Lalkuan line, servesTown, Lalkuan]
-
A.
Lalkuan
chosen
Lalkuan is a town in the Nainital district of Uttarakhand, India, known as a regional rail junction and gateway to the Kumaon region.
-
B.
Lalkurti
Lalkurti is a historic residential and commercial neighborhood in Rawalpindi, Pakistan, known for its colonial-era origins and proximity to the city’s main cantonment area.
-
C.
Laukaa
Laukaa is a municipality in Central Finland known for its lakes, rural landscapes, and proximity to the city of Jyväskylä.
-
D.
Larkollen
Larkollen is a coastal village in southeastern Norway known for its beaches, holiday homes, and maritime recreation.
-
E.
Lanklaar
Lanklaar is a village in the Belgian province of Limburg that forms part of the municipality of Maasmechelen.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178983fc8819080aa00e45ff77952 |
completed | April 29, 2026, 3:18 a.m. |
Created at: April 17, 2026, 3:13 p.m.