Triple
T36531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harold Stephen Black |
E723
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Black
Black is a common English-language surname borne by numerous notable individuals across diverse fields.
|
E5209
|
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: Black | Statement: [Harold Stephen Black, familyName, Black]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Black Context triple: [Harold Stephen Black, familyName, Black]
-
A.
Black
Black is a nominative report series of early United States Supreme Court decisions compiled and published under the name of the court reporter Black.
-
B.
Crimson
Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
-
C.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
D.
Black Americans
Black Americans are a racial and ethnic group in the United States descended largely from enslaved Africans, with a distinct cultural, historical, and political legacy that has profoundly shaped American society.
-
E.
Big Blue
Big Blue is the widely used nickname for the New York Giants, a professional American football team in the NFL.
- 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: Black Triple: [Harold Stephen Black, familyName, Black]
Generated description
Black is a common English-language surname borne by numerous notable individuals across diverse fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Black Target entity description: Black is a common English-language surname borne by numerous notable individuals across diverse fields.
-
A.
Black
Black is a nominative report series of early United States Supreme Court decisions compiled and published under the name of the court reporter Black.
-
B.
Crimson
Crimson is the collective name for Harvard University's varsity athletic teams competing in collegiate sports.
-
C.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
D.
Black Americans
Black Americans are a racial and ethnic group in the United States descended largely from enslaved Africans, with a distinct cultural, historical, and political legacy that has profoundly shaped American society.
-
E.
Big Blue
Big Blue is the widely used nickname for the New York Giants, a professional American football team in the NFL.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24acbb90881908c9f77e74034eb52 |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a255322d048190b3a45c6c6a80230c |
completed | Feb. 28, 2026, 2:38 a.m. |
| NEDg | Description generation | batch_69a255ee9c1c8190a9d1db89af34fbaf |
completed | Feb. 28, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a256a35c3081908aa5522c734bd54d |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.