Triple
T1133796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theodor Mommsen |
E23091
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mommsen
Mommsen is a German surname most famously associated with Theodor Mommsen, the Nobel Prize–winning historian and scholar of ancient Rome.
|
E131249
|
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: Mommsen | Statement: [Theodor Mommsen, familyName, Mommsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mommsen Context triple: [Theodor Mommsen, familyName, Mommsen]
-
A.
Bertramus
Bertramus is a Latinized variant of the given name Bertram, historically used in medieval and ecclesiastical contexts.
-
B.
Hammann
Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
-
C.
Hölldobler
Hölldobler is a German surname most notably associated with Bert Hölldobler, a prominent behavioral ecologist and myrmecologist known for his research on ants.
-
D.
Heinsius
Heinsius is a Dutch surname most notably associated with Anthonie Heinsius, a prominent statesman of the Dutch Republic in the late 17th and early 18th centuries.
-
E.
Morgenstern
Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
- 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: Mommsen Triple: [Theodor Mommsen, familyName, Mommsen]
Generated description
Mommsen is a German surname most famously associated with Theodor Mommsen, the Nobel Prize–winning historian and scholar of ancient Rome.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mommsen Target entity description: Mommsen is a German surname most famously associated with Theodor Mommsen, the Nobel Prize–winning historian and scholar of ancient Rome.
-
A.
Bertramus
Bertramus is a Latinized variant of the given name Bertram, historically used in medieval and ecclesiastical contexts.
-
B.
Hammann
Hammann is a German-origin surname borne by various notable individuals in fields such as aviation, music, and academia.
-
C.
Hölldobler
Hölldobler is a German surname most notably associated with Bert Hölldobler, a prominent behavioral ecologist and myrmecologist known for his research on ants.
-
D.
Heinsius
Heinsius is a Dutch surname most notably associated with Anthonie Heinsius, a prominent statesman of the Dutch Republic in the late 17th and early 18th centuries.
-
E.
Morgenstern
Morgenstern is a German surname borne by various notable figures in fields such as economics, literature, and the arts.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bbfe68008190b2307b8107f06a08 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac5ead716c81908bf7c6531cbff7f1 |
completed | March 7, 2026, 5:21 p.m. |
| NEDg | Description generation | batch_69ac5f2f566c8190a5630cee9c77e231 |
completed | March 7, 2026, 5:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac5fc6b6748190837a640623411eea |
completed | March 7, 2026, 5:26 p.m. |
Created at: March 1, 2026, 7:44 p.m.