Triple
T489729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold |
E9958
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Harrold
Harrold is a given name and surname, used as a variant spelling of Harold.
|
E64179
|
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: Harrold | Statement: [Harold, hasVariant, Harrold]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harrold Context triple: [Harold, hasVariant, Harrold]
-
A.
Hylton
Hylton is the defendant in the landmark 1796 U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
-
B.
Colsterworth
Colsterworth is a village in Lincolnshire, England, best known for its proximity to Woolsthorpe Manor, the birthplace of Sir Isaac Newton.
-
C.
Godalming
Godalming is a historic market town in southeast England known for its picturesque streets, riverside setting, and role as a commuter hub for London.
-
D.
Hillington
Hillington is a small village and civil parish in Norfolk, England, known for its rural setting and historic country estate, Hillington Hall.
-
E.
Baguley
Baguley is a suburban area in Wythenshawe, south Manchester, England, known primarily as a residential district with local transport links and amenities.
- 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: Harrold Triple: [Harold, hasVariant, Harrold]
Generated description
Harrold is a given name and surname, used as a variant spelling of Harold.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Harrold Target entity description: Harrold is a given name and surname, used as a variant spelling of Harold.
-
A.
Hylton
Hylton is the defendant in the landmark 1796 U.S. Supreme Court case Ware v. Hylton, which addressed the supremacy of federal treaties over conflicting state laws.
-
B.
Colsterworth
Colsterworth is a village in Lincolnshire, England, best known for its proximity to Woolsthorpe Manor, the birthplace of Sir Isaac Newton.
-
C.
Godalming
Godalming is a historic market town in southeast England known for its picturesque streets, riverside setting, and role as a commuter hub for London.
-
D.
Hillington
Hillington is a small village and civil parish in Norfolk, England, known for its rural setting and historic country estate, Hillington Hall.
-
E.
Baguley
Baguley is a suburban area in Wythenshawe, south Manchester, England, known primarily as a residential district with local transport links and amenities.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0e0a9648190b6a3b2da3a3b51e6 |
completed | Feb. 28, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a4a14aab308190b12deb3509e9715e |
completed | March 1, 2026, 8:27 p.m. |
| NEDg | Description generation | batch_69a4a27e8b7c8190991d3d5dc44c6913 |
completed | March 1, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a4a2d68b688190a5ec28394356d76c |
completed | March 1, 2026, 8:34 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.