Triple
T11385496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Wentworth Higginson |
E269705
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is the given name of Thomas Wentworth Higginson, a 19th-century American Unitarian minister, abolitionist, and supporter of women’s rights.
|
E922913
|
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 Wentworth Higginson, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Wentworth Higginson, givenName, Thomas]
-
A.
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.
-
B.
John
John is the given name of John Stewart, Earl of Mar, a Scottish nobleman and political figure.
-
C.
John
John is a fictional police detective and main character from the science fiction TV series "Almost Human."
-
D.
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.
-
E.
John
John is the given name of J. Gresham Machen, an influential early 20th-century American Presbyterian theologian and New Testament scholar.
- 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 Wentworth Higginson, givenName, Thomas]
Generated description
Thomas is the given name of Thomas Wentworth Higginson, a 19th-century American Unitarian minister, abolitionist, and supporter of women’s rights.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Target entity description: Thomas is the given name of Thomas Wentworth Higginson, a 19th-century American Unitarian minister, abolitionist, and supporter of women’s rights.
-
A.
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."
-
B.
Thomas
Thomas is the given name of Thomas Fairfax, 1st Lord Fairfax of Cameron, a prominent Parliamentarian general during the English Civil War.
-
C.
Thomas
Thomas is the given name of Thomas Cranmer, the 16th-century Archbishop of Canterbury and a leading figure in the English Reformation.
-
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 the British philosopher and political theorist T. H. Green, a key figure in 19th-century British Idealism.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7fc378d808190b587a044ede67e1e |
completed | April 9, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c1d4b188190b83cfad0cc95483e |
completed | April 20, 2026, 2:14 a.m. |
| NEDg | Description generation | batch_69e5932d3cb88190807acdcdc3aaa9fc |
completed | April 20, 2026, 2:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e59a0ab7e081908cb8761c4f82c664 |
completed | April 20, 2026, 3:14 a.m. |
Created at: April 8, 2026, 9:34 p.m.