Triple
T3912753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Old-Fashioned Girl |
E87360
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Sydney
Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
|
E402492
|
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: Sydney | Statement: [An Old-Fashioned Girl, mainCharacter, Sydney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sydney Context triple: [An Old-Fashioned Girl, mainCharacter, Sydney]
-
A.
Sydney
Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
-
B.
Melbourne
Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
-
C.
Melbourne
Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
-
D.
Melbourn
Melbourn is a village and civil parish in South Cambridgeshire, England, known for its historic architecture and rural community character.
-
E.
Brisbane
Brisbane is the capital and most populous city of the Australian state of Queensland, known for its subtropical climate, riverfront setting, and role as a major economic and cultural hub.
- 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: Sydney Triple: [An Old-Fashioned Girl, mainCharacter, Sydney]
Generated description
Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sydney Target entity description: Sydney is the spirited, fashionable young woman who serves as the central heroine of Louisa May Alcott’s novel "An Old-Fashioned Girl."
-
A.
Sydney
Sydney is Australia's largest and most populous city, renowned for its iconic harbour, Opera House, and Harbour Bridge.
-
B.
Melbourne
Melbourne is a major Australian city known for its vibrant arts scene, diverse culture, and status as a leading center for sports and education.
-
C.
Melbourne
Melbourne is a historic market town in Derbyshire, England, known for its Georgian architecture and the notable Melbourne Hall and gardens.
-
D.
Melbourn
Melbourn is a village and civil parish in South Cambridgeshire, England, known for its historic architecture and rural community character.
-
E.
Brisbane
Brisbane is a small city in northern San Mateo County, California, located just south of San Francisco on the lower slopes of San Bruno Mountain.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed37b19c81908e690c495d96607f |
completed | March 9, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5336ec05c8190ab632671bc1326c2 |
completed | March 14, 2026, 10:07 a.m. |
| NEDg | Description generation | batch_69b5341fb74081909a33753e5fdd5c32 |
completed | March 14, 2026, 10:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b534d279548190bee44aea7828ed3b |
completed | March 14, 2026, 10:13 a.m. |
Created at: March 9, 2026, 3:22 p.m.