Triple
T3011757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clair Huxtable |
E82237
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Clair
Clair is a feminine given name most famously associated with the character Clair Huxtable from the television series "The Cosby Show."
|
E317633
|
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: Clair | Statement: [Clair Huxtable, givenName, Clair]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clair Context triple: [Clair Huxtable, givenName, Clair]
-
A.
Clara
Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
-
B.
Clara
Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
-
C.
Cliffside
Cliffside is a residential neighbourhood in the eastern part of Toronto, Ontario, known for its proximity to the Scarborough Bluffs along Lake Ontario.
-
D.
Cline
Cline is a variant form of the surname Klein, commonly found in German-speaking and related communities.
-
E.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
- 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: Clair Triple: [Clair Huxtable, givenName, Clair]
Generated description
Clair is a feminine given name most famously associated with the character Clair Huxtable from the television series "The Cosby Show."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Clair Target entity description: Clair is a feminine given name most famously associated with the character Clair Huxtable from the television series "The Cosby Show."
-
A.
Clara
Clara is a feminine given name of Latin origin, derived from "clarus" meaning "bright" or "famous."
-
B.
Clara
Clara is a character in the American folk opera "Porgy and Bess," known as a young mother whose lullaby "Summertime" is one of the work’s most famous songs.
-
C.
Cliffside
Cliffside is a residential neighbourhood in the eastern part of Toronto, Ontario, known for its proximity to the Scarborough Bluffs along Lake Ontario.
-
D.
Cline
Cline is a variant form of the surname Klein, commonly found in German-speaking and related communities.
-
E.
Seabreeze
Seabreeze was a former neighboring city to Daytona Beach, Florida, that was eventually incorporated into the larger Daytona Beach municipality.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a66c334819082d1d320c48eca1b |
completed | March 8, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e6410e481909753bef34e053363 |
completed | March 11, 2026, 8:57 a.m. |
| NEDg | Description generation | batch_69b12f324fdc8190a279a773ef32ed01 |
completed | March 11, 2026, 9 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b1c641f3308190912252e5d5e4f843 |
completed | March 11, 2026, 7:45 p.m. |
Created at: March 8, 2026, 3 p.m.