Triple
T19410991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parasite (original score) |
E485584
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Camping |
—
|
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: Camping | Statement: [Parasite (original score), hasPart, Camping]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camping Context triple: [Parasite (original score), hasPart, Camping]
-
A.
Camping
chosen
Camping is an American comedy television series starring Jennifer Garner that follows a tightly wound woman whose meticulously planned outdoor trip unravels in chaotic and humorous ways.
-
B.
The Great Outdoors
"The Great Outdoors" is a work associated with Australian costume designer Lizzy Gardiner, likely showcasing her creative contributions to film or television.
-
C.
The Great Outdoors
The Great Outdoors is a 1988 comedy film starring John Candy and Dan Aykroyd about a family vacation gone hilariously wrong at a lakeside resort.
-
D.
Camp
Camp is a surname most notably associated with Garrett Camp, the Canadian entrepreneur and co-founder of Uber and StumbleUpon.
-
E.
Camp
Camp is a television series created by writer and producer Liz Heldens.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af4cc0c81909056b5e2ee574ab1 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.