Triple
T26489750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Møllehøj |
E669122
|
entity |
| Predicate | distanceToEjerBavnehøj |
P196581
|
FINISHED |
| Object | approximately 300 metres |
—
|
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: approximately 300 metres | Statement: [Møllehøj, distanceToEjerBavnehøj, approximately 300 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToEjerBavnehøj Context triple: [Møllehøj, distanceToEjerBavnehøj, approximately 300 metres]
-
A.
distanceFromLongyearbyen
Indicates the measured distance between a given location and Longyearbyen.
-
B.
distanceToBergen
Indicates the spatial distance between a given entity and the location Bergen.
-
C.
distanceFromArendal
Indicates the spatial distance between a given entity and the location of Arendal.
-
D.
distanceToBawtry
Indicates the spatial distance between a given entity and the location of Bawtry.
-
E.
distanceToFlensburg_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Flensburg.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fe5d58c3e48190910aa3c23485e2c4 |
completed | May 8, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69fe5c92090c8190bcfa412c0a3619df |
completed | May 8, 2026, 9:58 p.m. |
| PDg | Predicate description generation | batch_69fe5d580d7c819097cb18d438b01d08 |
completed | May 8, 2026, 10:02 p.m. |
Created at: April 27, 2026, 1:02 a.m.