Triple
T18163189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Parris |
E434818
|
entity |
| Predicate | hasPartIn |
P10186
|
FINISHED |
| Object | Thronecast |
—
|
NE NERFINISHED |
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: Thronecast | Statement: [Rachel Parris, hasPartIn, Thronecast]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thronecast Context triple: [Rachel Parris, hasPartIn, Thronecast]
-
A.
Thronecast
chosen
Thronecast is a British television aftershow that provided discussion, analysis, and fan interaction around episodes of the fantasy series Game of Thrones.
-
B.
Tank Stream
Tank Stream is a historic watercourse in central Sydney that once served as the colony’s primary freshwater supply and now runs mostly underground beneath the modern city.
-
C.
The Tom Show
The Tom Show is an American sitcom starring comedian Tom Arnold that aired in the late 1990s.
-
D.
AwesomenessTV
AwesomenessTV is a digital media and entertainment company known for producing youth-oriented online content, films, and television series.
-
E.
Twitch City
Twitch City is a Canadian cult-favorite dark comedy television series set in Toronto, known for its offbeat humor and eccentric characters.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec419788190a999a68f32fab39b |
completed | April 19, 2026, 1:55 p.m. |
Created at: April 10, 2026, 10:30 a.m.