Triple
T5394578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hallunda metro station |
E120619
|
entity |
| Predicate | distanceFromSlussen |
P62985
|
FINISHED |
| Object | 19.4 km |
—
|
LITERAL 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: 19.4 km | Statement: [Hallunda metro station, distanceFromSlussen, 19.4 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSlussen Context triple: [Hallunda metro station, distanceFromSlussen, 19.4 km]
-
A.
distanceFromOslo
Indicates the spatial distance between a given entity’s location and the city of Oslo.
-
B.
distanceFromStockholmCityCentre
Indicates the measured distance between a given location and the center of Stockholm city.
-
C.
distanceFromUppsala_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Uppsala.
-
D.
distanceFromCopenhagen
Indicates the spatial distance between a given entity and the location of Copenhagen.
-
E.
distanceToLappeenranta_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Lappeenranta.
- F. None of above. chosen
Provenance (4 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87441a208190b79561614759894b |
completed | March 20, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd853005088190b1b092a9beb090b2 |
completed | March 20, 2026, 5:34 p.m. |
Created at: March 20, 2026, 2:04 p.m.