Triple
T19268675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wah-Wah |
E481856
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Ruby Compton
Ruby Compton is a fictional character in the British coming-of-age film "Wah-Wah," which is set in 1960s Swaziland and explores family turmoil against the backdrop of the end of colonial rule.
|
E1436618
|
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: Ruby Compton | Statement: [Wah-Wah, hasCharacter, Ruby Compton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruby Compton Context triple: [Wah-Wah, hasCharacter, Ruby Compton]
-
A.
Ann Compton
Ann Compton is an American journalist best known for her long tenure as a White House correspondent for ABC News.
-
B.
Catherine Compton
Catherine Compton was a British aristocrat and the mother of Spencer Perceval, the only British prime minister to have been assassinated.
-
C.
Emily Berrington
Emily Berrington is a British actress best known for her role as the synth Niska in the television series "Humans."
-
D.
Ruby Holbrook
Ruby Holbrook was the wife of acclaimed American actor Hal Holbrook.
-
E.
Shiri Appleby
Shiri Appleby is an American actress best known for her lead role in the TV series "Roswell" and her later work on shows like "UnREAL."
- 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: Ruby Compton Triple: [Wah-Wah, hasCharacter, Ruby Compton]
Generated description
Ruby Compton is a fictional character in the British coming-of-age film "Wah-Wah," which is set in 1960s Swaziland and explores family turmoil against the backdrop of the end of colonial rule.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruby Compton Target entity description: Ruby Compton is a fictional character in the British coming-of-age film "Wah-Wah," which is set in 1960s Swaziland and explores family turmoil against the backdrop of the end of colonial rule.
-
A.
Ann Compton
Ann Compton is an American journalist best known for her long tenure as a White House correspondent for ABC News.
-
B.
Catherine Compton
Catherine Compton was a British aristocrat and the mother of Spencer Perceval, the only British prime minister to have been assassinated.
-
C.
Emily Berrington
Emily Berrington is a British actress best known for her role as the synth Niska in the television series "Humans."
-
D.
Ruby Holbrook
Ruby Holbrook was the wife of acclaimed American actor Hal Holbrook.
-
E.
Shiri Appleby
Shiri Appleby is an American actress best known for her lead role in the TV series "Roswell" and her later work on shows like "UnREAL."
- 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_69d8e8ce54cc8190998418ff1f66ef28 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fbb68d0c819083ba0ce680dd7d99 |
completed | April 20, 2026, 10:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08a544bcc081908db3128bc107e5dc |
completed | May 16, 2026, 5:11 p.m. |
| NEDg | Description generation | batch_6a08a5de7b388190a03defa5ac8df667 |
completed | May 16, 2026, 5:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08a67f37f08190a50c377042c44a6f |
completed | May 16, 2026, 5:16 p.m. |
Created at: April 10, 2026, 1:29 p.m.