Triple
T34949653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madura |
E1007953
|
entity |
| Predicate | distanceToNorseman_km |
P206751
|
FINISHED |
| Object | approximately 550 |
—
|
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 550 | Statement: [Madura, distanceToNorseman_km, approximately 550]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNorseman_km Context triple: [Madura, distanceToNorseman_km, approximately 550]
-
A.
distanceToTromsø_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the location of Tromsø.
-
B.
distanceFromKristiansand
Indicates the spatial distance between a given location or object and the city of Kristiansand.
-
C.
distanceToBirka
Indicates the spatial distance between a given entity and the location Birka.
-
D.
distanceFromOslo
Indicates the spatial distance between a given entity’s location and the city of Oslo.
-
E.
distanceFromStavanger
Indicates the spatial distance between a given entity or location and the city of Stavanger.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4 p.m.