Triple
T22683350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | island of Hven |
E560840
|
entity |
| Predicate | locatedBetweenCities |
P36168
|
FINISHED |
| Object | Landskrona and Copenhagen |
—
|
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: Landskrona and Copenhagen | Statement: [island of Hven, locatedBetweenCities, Landskrona and Copenhagen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedBetweenCities Context triple: [island of Hven, locatedBetweenCities, Landskrona and Copenhagen]
-
A.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
B.
betweenCity
chosen
Indicates a spatial relationship where one entity is located in the area or position separating two specified cities.
-
C.
locatedBetweenStreets
Indicates that something is situated between two specified streets, with its position bounded or defined by those streets.
-
D.
locatedInCityWithSignificance
Indicates that an entity is located in a city that holds particular importance or notable significance (e.g., historical, cultural, political, or economic).
-
E.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
- F. None of above.
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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1786204d88190a837a5f04e16e94c |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:12 p.m.