Triple
T10839294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Babington Macaulay |
E255843
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is a masculine given name of Aramaic origin, widely used in English-speaking countries and historically borne by numerous notable religious, political, and literary figures.
|
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 Babington Macaulay, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Babington Macaulay, givenName, Thomas]
-
A.
John
John IV of Portugal was a 17th-century Portuguese king who restored the country's independence from Spain and founded the Braganza dynasty.
-
B.
John
John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
-
C.
John
John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
-
D.
John
John was a historical Prince of Asturias, the traditional title for the heir apparent to the Spanish throne.
-
E.
John
John is the given name of John Copley, 1st Baron Lyndhurst, a prominent 19th-century British lawyer and politician who served three times as Lord Chancellor.
- 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 Babington Macaulay, givenName, Thomas]
Generated description
Thomas is a masculine given name of Aramaic origin, widely used in English-speaking countries and historically borne by numerous notable religious, political, and literary figures.
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 English-speaking countries and historically borne by numerous notable religious, political, and literary figures.
-
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 first name of English actor Tom Sturridge, known for his work in film, television, and theatre.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d747012fa48190af06de2cfb231d5b |
completed | April 9, 2026, 6:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7c0907c8190b092bb6754fe4e52 |
completed | April 15, 2026, 8:40 p.m. |
| NEDg | Description generation | batch_69e0026e7900819087327db5f625169c |
completed | April 15, 2026, 9:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e0057a7704819096becb74dc261883 |
completed | April 15, 2026, 9:39 p.m. |
Created at: April 8, 2026, 9:19 p.m.