Triple
T10595506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arcadia (play) |
E250101
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Thomasina Coverly
Thomasina Coverly is a precociously brilliant young mathematician and central character in Tom Stoppard’s play "Arcadia," whose insights anticipate modern chaos theory and thermodynamics.
|
E873514
|
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: Thomasina Coverly | Statement: [Arcadia (play), hasCharacter, Thomasina Coverly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thomasina Coverly Context triple: [Arcadia (play), hasCharacter, Thomasina Coverly]
-
A.
Thomasina Hamilton
Thomasina Hamilton is the feminine form of the personal name Thomas Hamilton.
-
B.
Effie Wolfe
Effie Wolfe was a member of the Wolfe family and the sister of American novelist Thomas Wolfe.
-
C.
Elizabeth Marsh
Elizabeth Marsh was the wife of American engineer Willis Carrier, the inventor widely credited with creating modern air conditioning.
-
D.
Ambrosine Phillpotts
Ambrosine Phillpotts was a British character actress known for her numerous supporting roles in mid-20th-century film, theatre, and television.
-
E.
Celia
Celia is a feminine given name of Latin origin, commonly used in English-speaking countries.
- 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: Thomasina Coverly Triple: [Arcadia (play), hasCharacter, Thomasina Coverly]
Generated description
Thomasina Coverly is a precociously brilliant young mathematician and central character in Tom Stoppard’s play "Arcadia," whose insights anticipate modern chaos theory and thermodynamics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thomasina Coverly Target entity description: Thomasina Coverly is a precociously brilliant young mathematician and central character in Tom Stoppard’s play "Arcadia," whose insights anticipate modern chaos theory and thermodynamics.
-
A.
Thomasina Hamilton
Thomasina Hamilton is the feminine form of the personal name Thomas Hamilton.
-
B.
Effie Wolfe
Effie Wolfe was a member of the Wolfe family and the sister of American novelist Thomas Wolfe.
-
C.
Elizabeth Marsh
Elizabeth Marsh was the wife of American engineer Willis Carrier, the inventor widely credited with creating modern air conditioning.
-
D.
Ambrosine Phillpotts
Ambrosine Phillpotts was a British character actress known for her numerous supporting roles in mid-20th-century film, theatre, and television.
-
E.
Celia
Celia is a feminine given name of Latin origin, commonly used in English-speaking countries.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5278cbf9081909ef419b0144d5019 |
completed | April 7, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e8de2e88190835954abb2ac2ece |
completed | April 10, 2026, 8:33 p.m. |
| NEDg | Description generation | batch_69d95f80d0c48190b88e3a4b3e42279c |
completed | April 10, 2026, 8:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9602a1d688190ad0f3014d69049cc |
completed | April 10, 2026, 8:40 p.m. |
Created at: April 6, 2026, 12:41 p.m.