Triple
T793824
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikael Agricola |
E16973
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Mikael
Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
|
E99056
|
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: Mikael | Statement: [Mikael Agricola, givenName, Mikael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikael Context triple: [Mikael Agricola, givenName, Mikael]
-
A.
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.
-
B.
Mikael Salomon
Mikael Salomon is a Danish cinematographer and film director known for his visually striking work on major Hollywood films and television series.
-
C.
Erik Neander
Erik Neander is a Major League Baseball executive known for leading the Tampa Bay Rays’ front office and overseeing the club’s baseball operations and roster construction.
-
D.
Gunnar
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
-
E.
Svante
Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
- 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: Mikael Triple: [Mikael Agricola, givenName, Mikael]
Generated description
Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mikael Target entity description: Mikael is a masculine given name commonly used in Scandinavian and Finnish cultures, equivalent to Michael.
-
A.
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.
-
B.
Mikael Salomon
Mikael Salomon is a Danish cinematographer and film director known for his visually striking work on major Hollywood films and television series.
-
C.
Erik Neander
Erik Neander is a Major League Baseball executive known for leading the Tampa Bay Rays’ front office and overseeing the club’s baseball operations and roster construction.
-
D.
Gunnar
Gunnar is a masculine given name of Old Norse origin, commonly used in Scandinavian countries and associated with warriors or bold fighters.
-
E.
Svante
Svante is the given name of Swedish geneticist Svante Pääbo, a Nobel Prize–winning pioneer in the field of paleogenomics.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79b976c819085cd381bbd597ca5 |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a792892a588190b15b0cb95c431084 |
completed | March 4, 2026, 2:01 a.m. |
| NEDg | Description generation | batch_69a79335d99c819098c72e7a86ad1130 |
completed | March 4, 2026, 2:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a793c612d88190bce254142bd75f67 |
completed | March 4, 2026, 2:07 a.m. |
Created at: March 1, 2026, 7:38 p.m.