Triple
T15357790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tegan Quin |
E367206
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Tegan Rain Quin |
E367206
|
NE FINISHED |
How this triple was built (2 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: Tegan Rain Quin | Statement: [Tegan Quin, birthName, Tegan Rain Quin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tegan Rain Quin Context triple: [Tegan Quin, birthName, Tegan Rain Quin]
-
A.
Tegan Quin
chosen
Tegan Quin is a Canadian singer-songwriter best known as one half of the indie pop duo Tegan and Sara.
-
B.
Tegan West
Tegan West is an American actor and screenwriter best known for his role in the Vietnam War film "Hamburger Hill" and for co-writing several film and television projects.
-
C.
Tegan Jovanka
Tegan Jovanka is a brash, outspoken Australian airline stewardess who serves as one of the Fifth Doctor’s companions in the classic British science fiction series Doctor Who.
-
D.
Amy Wren
Amy Wren is a British actress known for her television roles, including a prominent part in the comedy-drama series "Sirens."
-
E.
Kylie Bunbury
Kylie Bunbury is a Canadian-American actress best known for her roles in television series such as "Pitch," "Big Sky," and "Under the Dome."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2d4934819097fc63603964217c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cec4f2481908fae5209bfd48dcf |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:18 a.m.