Triple
T1830473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauri Kristian Relander |
E40750
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Relander
Relander is a Finnish surname most notably associated with Lauri Kristian Relander, the second President of Finland.
|
E203473
|
NE FINISHED |
How this triple was built (4 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: Relander | Statement: [Lauri Kristian Relander, familyName, Relander]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Relander Context triple: [Lauri Kristian Relander, familyName, Relander]
-
A.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
B.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
C.
Dellner
Dellner is a company specializing in railway coupling and connection systems used on modern passenger and freight trains worldwide.
-
D.
Lanman
Lanman is a surname most notably associated with American philanthropist William K. Lanman Jr., a major benefactor of Yale University.
-
E.
Larrelt
Larrelt is a district of the German seaport city of Emden in Lower Saxony.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Relander Triple: [Lauri Kristian Relander, familyName, Relander]
Generated description
Relander is a Finnish surname most notably associated with Lauri Kristian Relander, the second President of Finland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Relander Target entity description: Relander is a Finnish surname most notably associated with Lauri Kristian Relander, the second President of Finland.
-
A.
Lorens
Lorens is a character from Paulo Coelho’s novel "Brida," serving as one of the key figures in the protagonist’s spiritual and personal journey.
-
B.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
C.
Dellner
Dellner is a company specializing in railway coupling and connection systems used on modern passenger and freight trains worldwide.
-
D.
Lanman
Lanman is a surname most notably associated with American philanthropist William K. Lanman Jr., a major benefactor of Yale University.
-
E.
Larrelt
Larrelt is a district of the German seaport city of Emden in Lower Saxony.
- F. None of above. chosen
Provenance (5 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0144cc08190abd1a6cf44e64daf |
completed | March 7, 2026, 4:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf6d49988190b8cb1773609a379b |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adc07fff60819092b10dd0e417ac5a |
completed | March 8, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc0fd79c48190864f53a90517edc6 |
completed | March 8, 2026, 6:33 p.m. |
Created at: March 4, 2026, 7:32 p.m.