Triple
T17876465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binky Barnes |
E446965
|
entity |
| Predicate | hasYoungerSister |
P31639
|
FINISHED |
| Object |
Mei Lin Barnes
Mei Lin Barnes is a minor character in the children's animated series "Arthur," known as the baby sister of Binky Barnes.
|
E1293384
|
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: Mei Lin Barnes | Statement: [Binky Barnes, hasYoungerSister, Mei Lin Barnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mei Lin Barnes Context triple: [Binky Barnes, hasYoungerSister, Mei Lin Barnes]
-
A.
Rachel Fong
Rachel Fong is a researcher in machine learning and reinforcement learning, known for her work on the Hindsight Experience Replay technique.
-
B.
Amy Chiang
Amy Chiang is a member of Taiwan’s influential Chiang family, known primarily as a daughter of former President Chiang Ching-kuo.
-
C.
Karen Kwan
Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
-
D.
Laureen Chew
Laureen Chew is an actress best known for her role in the influential 1982 Asian American independent film "Chan Is Missing."
-
E.
Eileen Loo
Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
- 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: Mei Lin Barnes Triple: [Binky Barnes, hasYoungerSister, Mei Lin Barnes]
Generated description
Mei Lin Barnes is a minor character in the children's animated series "Arthur," known as the baby sister of Binky Barnes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mei Lin Barnes Target entity description: Mei Lin Barnes is a minor character in the children's animated series "Arthur," known as the baby sister of Binky Barnes.
-
A.
Rachel Fong
Rachel Fong is a researcher in machine learning and reinforcement learning, known for her work on the Hindsight Experience Replay technique.
-
B.
Amy Chiang
Amy Chiang is a member of Taiwan’s influential Chiang family, known primarily as a daughter of former President Chiang Ching-kuo.
-
C.
Karen Kwan
Karen Kwan is an American figure skater and the older sister of Olympic medalist Michelle Kwan.
-
D.
Laureen Chew
Laureen Chew is an actress best known for her role in the influential 1982 Asian American independent film "Chan Is Missing."
-
E.
Eileen Loo
Eileen Loo was the wife of renowned Chinese-American architect I. M. Pei and a supportive partner throughout his celebrated career.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa614b48190bdc9e905e9e6d5e0 |
completed | April 19, 2026, 9:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0313d1c1e48190a17e3b81c4ee22f3 |
completed | May 12, 2026, 11:49 a.m. |
| NEDg | Description generation | batch_6a031485c3908190a8fe49068d45e910 |
completed | May 12, 2026, 11:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03151de8408190a4c8bc30f5606951 |
completed | May 12, 2026, 11:55 a.m. |
Created at: April 10, 2026, 10:18 a.m.