Triple
T2260744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moses Cleaveland |
E50032
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Esther Champion
Esther Champion was the wife of Moses Cleaveland, the American surveyor and founder of the city of Cleveland, Ohio.
|
E263291
|
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: Esther Champion | Statement: [Moses Cleaveland, spouse, Esther Champion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esther Champion Context triple: [Moses Cleaveland, spouse, Esther Champion]
-
A.
Esther Harvey
Esther Harvey was the wife of renowned American Broadway baritone and actor Alfred Drake.
-
B.
Esther Ross
Esther Ross was the woman who served as the sponsor and ceremonial namesake figure for the U.S. Navy battleship USS Arizona (BB-39) at its christening.
-
C.
Esther Smith
Esther Smith is the central teenage daughter in the classic 1944 MGM musical film "Meet Me in St. Louis," famously portrayed by Judy Garland.
-
D.
Esther Drummond
Esther Drummond is a CIA analyst who becomes a key member of the Torchwood team in the science fiction television series "Torchwood: Miracle Day."
-
E.
Esther Bubley
Esther Bubley was an American documentary photographer best known for her intimate, human-centered images of everyday life in mid-20th-century America, particularly during and after World War II.
- 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: Esther Champion Triple: [Moses Cleaveland, spouse, Esther Champion]
Generated description
Esther Champion was the wife of Moses Cleaveland, the American surveyor and founder of the city of Cleveland, Ohio.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Esther Champion Target entity description: Esther Champion was the wife of Moses Cleaveland, the American surveyor and founder of the city of Cleveland, Ohio.
-
A.
Esther Harvey
Esther Harvey was the wife of renowned American Broadway baritone and actor Alfred Drake.
-
B.
Esther Ross
Esther Ross was the woman who served as the sponsor and ceremonial namesake figure for the U.S. Navy battleship USS Arizona (BB-39) at its christening.
-
C.
Esther Smith
Esther Smith is the central teenage daughter in the classic 1944 MGM musical film "Meet Me in St. Louis," famously portrayed by Judy Garland.
-
D.
Esther Drummond
Esther Drummond is a CIA analyst who becomes a key member of the Torchwood team in the science fiction television series "Torchwood: Miracle Day."
-
E.
Esther Bubley
Esther Bubley was an American documentary photographer best known for her intimate, human-centered images of everyday life in mid-20th-century America, particularly during and after World War II.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc18aa9d48190893ca32558730e9c |
completed | March 7, 2026, 6:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3b7380c8190b1a70f7032c442a5 |
completed | March 9, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_69aeb3fdccbc8190a3abe90ba1206bc6 |
completed | March 9, 2026, 11:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeb48f5d74819083dd1dfafc5a958a |
completed | March 9, 2026, 11:52 a.m. |
Created at: March 4, 2026, 7:48 p.m.