Triple
T15357791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tegan Quin |
E367206
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tegan |
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 | Statement: [Tegan Quin, givenName, Tegan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tegan Context triple: [Tegan Quin, givenName, Tegan]
-
A.
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.
-
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 Quin
chosen
Tegan Quin is a Canadian singer-songwriter best known as one half of the indie pop duo Tegan and Sara.
-
D.
Tilly
Tilly is one of the short stories included in James Joyce’s collection *Pomes Penyeach*.
-
E.
Tilly
Tilly is the commonly used name for Johann Tserclaes, Count of Tilly, a prominent general of the Catholic League during the early stages of the Thirty Years' War.
- 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_69ff364d82c48190b116528b5c00e918 |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:18 a.m.