Triple
T11588691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haarajoki railway station |
E274820
|
entity |
| Predicate | fareZone |
P844
|
FINISHED |
| Object | HSL zone D |
E410284
|
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: HSL zone D | Statement: [Haarajoki railway station, fareZone, HSL zone D]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HSL zone D Context triple: [Haarajoki railway station, fareZone, HSL zone D]
-
A.
HSL 4
HSL 4 is a Belgian high-speed railway line that connects Antwerp to the Dutch border as part of the international high-speed rail corridor between Brussels and Amsterdam.
-
B.
HSL
HSL is the three-letter National Rail station code for Haslemere railway station in Surrey, England.
-
C.
HSL
chosen
HSL is the public transport authority responsible for planning and organizing bus, tram, metro, commuter rail, and ferry services in the Helsinki metropolitan area of Finland.
-
D.
HSL 3
HSL 3 is a Belgian high-speed railway line that connects Liège to the German border as part of the international high-speed rail corridor between Brussels and Germany.
-
E.
HSL 2
HSL 2 is a Belgian high-speed railway line primarily used for fast passenger services between major cities and international connections.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89463360c8190b91228c46bfe2e5f |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e71451f1388190b72d7b755d198999 |
completed | April 21, 2026, 6:08 a.m. |
Created at: April 8, 2026, 9:38 p.m.