Triple
T22080625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Shirley |
E545638
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object |
Shirley
Shirley is a surname most famously associated with Anne Shirley, the imaginative heroine of L. M. Montgomery’s "Anne of Green Gables" series.
|
E20376
|
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: Shirley | Statement: [Anne Shirley, hasSurname, Shirley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shirley Context triple: [Anne Shirley, hasSurname, Shirley]
-
A.
Shirley
Shirley is a residential and commercial district within the city of Southampton in Hampshire, England.
-
B.
Shirley
Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
-
C.
Shirley
"Shirley" is a social and political novel by Charlotte Brontë set during the industrial unrest of early 19th-century England, exploring themes of class conflict, gender roles, and economic hardship.
-
D.
Shirley
Shirley is a suburban area in the London Borough of Croydon, known for its residential neighborhoods and proximity to green spaces and nearby districts like West Wickham.
-
E.
Shirley
Shirley is a devout, long-suffering matriarch in Tyler Perry’s "Madea’s Big Happy Family," whose illness and desire to reunite her fractured family drive much of the film’s emotional core.
- 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: Shirley Triple: [Anne Shirley, hasSurname, Shirley]
Generated description
Shirley is a surname most famously associated with Anne Shirley, the imaginative heroine of L. M. Montgomery’s "Anne of Green Gables" series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Shirley Target entity description: Shirley is a surname most famously associated with Anne Shirley, the imaginative heroine of L. M. Montgomery’s "Anne of Green Gables" series.
-
A.
Shirley
chosen
Shirley is an English surname of Old English origin that has also become a common given name.
-
B.
Shirley
Shirley is the given first name of the American actress Shelley Winters, a prominent figure in mid-20th-century cinema.
-
C.
Shirley
Shirley is the given first name of the English actress Amanda Barrie, known for her roles in British film and television.
-
D.
Shirley
Shirley is the given name of Shirley Ann Jackson, a prominent American physicist and trailblazing academic leader.
-
E.
Shirley
Shirley is one of Count Olaf’s many disguises in Lemony Snicket’s "A Series of Unfortunate Events," used as part of his schemes against the Baudelaire orphans.
- F. None of above.
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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b6338481908e6bb0187cdd42af |
completed | April 28, 2026, 9:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a80bb65fc8190a224994ef7ab50d1 |
completed | May 18, 2026, 3 a.m. |
| NEDg | Description generation | batch_6a0a81c335e08190ae941d7ebce6688e |
completed | May 18, 2026, 3:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a828694988190bf07e1b649a109f3 |
completed | May 18, 2026, 3:07 a.m. |
Created at: April 16, 2026, 8:28 p.m.