Triple
T10707319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Pelham, 1st Baron Pelham |
E252440
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Thomas
Thomas is the given name of Thomas Pelham, 1st Baron Pelham, an English Whig politician of the late 17th and early 18th centuries.
|
E881554
|
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 Pelham, 1st Baron Pelham, givenName, Thomas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomas Context triple: [Thomas Pelham, 1st Baron Pelham, givenName, Thomas]
-
A.
John
John is the first name of Pete Ricketts, an American businessman and politician who has served as governor of Nebraska.
-
B.
John
John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
-
C.
John
John is the given name of Colonel John Quincy, an American military officer and politician after whom John Quincy Adams was named.
-
D.
John
John is the given name of John Stewart, Earl of Mar, a Scottish nobleman and political figure.
-
E.
John
John is a fictional police detective and main character from the science fiction TV series "Almost Human."
- 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 Pelham, 1st Baron Pelham, givenName, Thomas]
Generated description
Thomas is the given name of Thomas Pelham, 1st Baron Pelham, an English Whig politician of the late 17th and early 18th centuries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomas Target entity description: Thomas is the given name of Thomas Pelham, 1st Baron Pelham, an English Whig politician of the late 17th and early 18th centuries.
-
A.
Thomas
Thomas is the given name of Thomas Pelham-Holles, 1st Duke of Newcastle, a prominent 18th-century British Whig statesman and prime minister.
-
B.
Thomas
Thomas is the given name of Thomas Osborne, 1st Duke of Leeds, a prominent 17th-century English statesman and politician.
-
C.
Thomas
Thomas is the given name of Thomas Fairfax, 1st Lord Fairfax of Cameron, a prominent Parliamentarian general during the English Civil War.
-
D.
Thomas
Thomas is the given name of Thomas Pitt, 1st Baron Camelford, a British naval officer and aristocrat known for his volatile temperament in the late 18th and early 19th centuries.
-
E.
Thomas
Thomas is the given name of Thomas Cochrane, 10th Earl of Dundonald, a renowned British naval officer and radical politician of the 19th century.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fde080d48190830eaa863aad61ff |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbacd1f88081908e65e9092acc2a56 |
completed | April 12, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69dbaeb211088190a9118c71918584e5 |
completed | April 12, 2026, 2:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dbaf7c999c819097a8cdf5bd82f648 |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 8, 2026, 9:12 p.m.