Triple
T6376316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Wolff |
E143473
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is a masculine given name of Aramaic origin, widely used in many languages and historically associated with Christian tradition.
|
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 Wolff, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Wolff, givenName, Thomas]
-
A.
Thomas
Thomas is the middle name of Edward Thomas Wailes, an American diplomat.
-
B.
Thomas
Thomas is the given first name of the renowned American playwright Tennessee Williams, known for works such as "A Streetcar Named Desire" and "Cat on a Hot Tin Roof."
-
C.
Thomas
Thomas is the middle name of William T. Sampson, a notable U.S. Navy admiral from the Spanish–American War era.
-
D.
Thomas
Thomas is the given first name of American astronaut Ken Mattingly, known for his role in the Apollo and Space Shuttle programs.
-
E.
Thomas
Thomas is the given name of Sir Thomas Blamey, an Australian field marshal and senior military commander during World War II.
- 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 Wolff, givenName, Thomas]
Generated description
Thomas is a masculine given name of Aramaic origin, widely used in many languages and historically associated with Christian tradition.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Target entity description: Thomas is a masculine given name of Aramaic origin, widely used in many languages and historically associated with Christian tradition.
-
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 name of Thomas Malthus, the influential English economist and demographer known for his theories on population growth and resource limits.
-
E.
Thomas
Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0683bfc7081908b15c3c9a3c72e7b |
completed | March 22, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64ba5b0bc8190aefa07c77c99be83 |
completed | March 27, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_69c64f37cfa88190a1b896d1893a28d4 |
completed | March 27, 2026, 9:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c64fa0196c8190aa4c7241acf0c0b6 |
completed | March 27, 2026, 9:36 a.m. |
Created at: March 22, 2026, 4:33 p.m.