Triple
T999710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivar Tengbom |
E21575
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Ivar
Ivar is a masculine given name of Old Norse origin, traditionally used in Scandinavian countries.
|
E118767
|
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: Ivar | Statement: [Ivar Tengbom, givenName, Ivar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivar Context triple: [Ivar Tengbom, givenName, Ivar]
-
A.
Gunnar
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
-
B.
Johan
Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
-
C.
Hrólfr
Hrólfr, better known as Rollo, was a Viking leader who became the first ruler of Normandy in the early 10th century.
-
D.
Audun Tron
Audun Tron is a Norwegian politician who served as the mayor of Lillehammer during the period when the city hosted the 1994 Winter Olympics.
-
E.
Halvdan Koht
Halvdan Koht was a prominent Norwegian historian, politician, and former foreign minister known for his influential role in early 20th-century Norwegian academic and political life.
- 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: Ivar Triple: [Ivar Tengbom, givenName, Ivar]
Generated description
Ivar is a masculine given name of Old Norse origin, traditionally used in Scandinavian countries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ivar Target entity description: Ivar is a masculine given name of Old Norse origin, traditionally used in Scandinavian countries.
-
A.
Gunnar
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
-
B.
Johan
Johan is the given first name of J. Erik Jonsson, an American businessman and philanthropist who co-founded Texas Instruments and served as mayor of Dallas.
-
C.
Hrólfr
Hrólfr, better known as Rollo, was a Viking leader who became the first ruler of Normandy in the early 10th century.
-
D.
Audun Tron
Audun Tron is a Norwegian politician who served as the mayor of Lillehammer during the period when the city hosted the 1994 Winter Olympics.
-
E.
Halvdan Koht
Halvdan Koht was a prominent Norwegian historian, politician, and former foreign minister known for his influential role in early 20th-century Norwegian academic and political life.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4e3d8b081908e536928e7d6199d |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a1aab68819091537958818fce48 |
completed | March 7, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_69ac2a9b66b48190a3c14c431fe41c1e |
completed | March 7, 2026, 1:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac2b18ea44819086cd9ead0d8e0d01 |
completed | March 7, 2026, 1:41 p.m. |
Created at: March 1, 2026, 7:41 p.m.