Triple
T15244683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard With |
E364348
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Trondheim, Norway |
E136993
|
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: Trondheim, Norway | Statement: [Richard With, placeOfDeath, Trondheim, Norway]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trondheim, Norway Context triple: [Richard With, placeOfDeath, Trondheim, Norway]
-
A.
Trondheim
chosen
Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
-
B.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
C.
Oslo
Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
-
D.
Stavanger
Stavanger is a coastal city in southwestern Norway known for its oil industry hub status, historic wooden houses, and proximity to natural attractions like the Lysefjord and Preikestolen.
-
E.
Bergen, Sweden
Bergen, Sweden is a small locality in Västra Götaland County known for its rural character and twinning relationship with Bergen, Germany.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f306f08190be448b215d6c9b6c |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f24967c8190b0bdb84b88a0aaa3 |
completed | May 9, 2026, 4:21 p.m. |
Created at: April 10, 2026, 3:13 a.m.