Triple
T15501217
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red line (Stockholm metro) |
E378957
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object | Fruängen |
E1134018
|
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: Fruängen | Statement: [Red line (Stockholm metro), hasTerminus, Fruängen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fruängen Context triple: [Red line (Stockholm metro), hasTerminus, Fruängen]
-
A.
Fruängen
chosen
Fruängen is a Stockholm metro station on the red line, serving as the terminus of one of its southern branches in the Fruängen district.
-
B.
Lány
Lány is a village and chateau area in the Czech Republic known as the site of the presidential summer residence and the place where the first Czechoslovak president Tomáš Garrigue Masaryk died.
-
C.
Lillafüred
Lillafüred is a scenic resort area in northern Hungary known for its historic palace hotel, hanging gardens, and proximity to natural attractions like caves and waterfalls.
-
D.
Tjejvasan
Tjejvasan is a popular women-only cross-country ski race in Sweden that forms part of the larger Vasaloppet series.
-
E.
Majgull
Majgull is a Swedish given name, notably borne by the acclaimed author Majgull Axelsson.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcb4e8c81908e4ab463e3ae252b |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3669f908819087162b1b8a4e4320 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:54 a.m.