Triple
T9845047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Südhof |
E239319
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is a common masculine given name of Aramaic origin, widely used in many languages and cultures.
|
E67625
|
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: Thomas | Statement: [Thomas Südhof, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Südhof, givenName, Thomas]
-
A.
John
John is the husband of Martha Rainsborough.
-
B.
John
John is the given name of Colonel John Quincy, an American military officer and politician after whom John Quincy Adams was named.
-
C.
John
John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
-
D.
John
John is the given name of John Vlissides, a software engineer best known as one of the “Gang of Four” authors of the influential book *Design Patterns: Elements of Reusable Object-Oriented Software*.
-
E.
John
John I, Count Palatine of Simmern, was a 15th-century German nobleman of the House of Wittelsbach who ruled the Palatinate-Simmern region within the Holy Roman Empire.
- 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: Thomas Triple: [Thomas Südhof, givenName, Thomas]
Generated description
Thomas is a common masculine given name of Aramaic origin, widely used in many languages and cultures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Target entity description: Thomas is a common masculine given name of Aramaic origin, widely used in many languages and cultures.
-
A.
Thomas
chosen
Thomas is a common masculine given name of Aramaic origin, widely used in English-speaking and many other cultures.
-
B.
Thomas
Thomas is a common surname of English and Welsh origin, derived from the given name Thomas and borne by numerous notable individuals worldwide.
-
C.
Thomas
Thomas is the given name of Thomas Paine, the influential 18th-century political philosopher and writer known for works like "Common Sense" and "The Rights of Man."
-
D.
Thomas
Thomas is the given first name of English actor Tom Sturridge, known for his work in film, television, and theatre.
-
E.
Thomas
Thomas is the given name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
- F. None of above.
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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb35ff7848190a8a717773d8654b9 |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1ead49b14819086a9bbd256f298a9 |
completed | April 5, 2026, 4:53 a.m. |
| NEDg | Description generation | batch_69d1eb79be388190853e0e7c29287294 |
completed | April 5, 2026, 4:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1ebf0a99081908ae0c4bceadc42bc |
completed | April 5, 2026, 4:58 a.m. |
Created at: March 30, 2026, 8:33 p.m.