Triple
T326408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Pitt |
E6528
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Diamond Pitt
Diamond Pitt is the nickname of Thomas Pitt, a prominent 17th–18th century English merchant and politician famed for amassing great wealth through the diamond trade.
|
E42252
|
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: Diamond Pitt | Statement: [Thomas Pitt, nickname, Diamond Pitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diamond Pitt Context triple: [Thomas Pitt, nickname, Diamond Pitt]
-
A.
Blacker
Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
-
B.
Blatch
Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
-
C.
Stumptown
Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
-
D.
Clemmie
Clemmie is a diminutive given name commonly used as a nickname for Clementine.
-
E.
Little Brother
Little Brother is a young adult cyberpunk novel by Cory Doctorow that follows a teenage hacker fighting government surveillance in a near-future San Francisco.
- 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: Diamond Pitt Triple: [Thomas Pitt, nickname, Diamond Pitt]
Generated description
Diamond Pitt is the nickname of Thomas Pitt, a prominent 17th–18th century English merchant and politician famed for amassing great wealth through the diamond trade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Diamond Pitt Target entity description: Diamond Pitt is the nickname of Thomas Pitt, a prominent 17th–18th century English merchant and politician famed for amassing great wealth through the diamond trade.
-
A.
Blacker
Blacker is a comparative form of the color term "black," indicating a greater degree of darkness or blackness.
-
B.
Blatch
Blatch is the surname of Nora Stanton Blatch, an early 20th-century American civil engineer, suffragist, and women's rights activist.
-
C.
Stumptown
Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
-
D.
Clemmie
Clemmie is a diminutive given name commonly used as a nickname for Clementine.
-
E.
Little Brother
Little Brother is a young adult cyberpunk novel by Cory Doctorow that follows a teenage hacker fighting government surveillance in a near-future San Francisco.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea974d8481908c7d84f72a7728b6 |
completed | Feb. 28, 2026, 1:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3cfec426081908a0c7e968846515a |
completed | March 1, 2026, 5:34 a.m. |
| NEDg | Description generation | batch_69a3d0babef081909813c4189e996803 |
completed | March 1, 2026, 5:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3d144f09c81908a1d7df72a3b0bbc |
completed | March 1, 2026, 5:40 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.