Triple
T19907404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Negative |
E478454
|
entity |
| Predicate | precedesInSeries |
P11124
|
FINISHED |
| Object | The Print |
—
|
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: The Print | Statement: [The Negative, precedesInSeries, The Print]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Print Context triple: [The Negative, precedesInSeries, The Print]
-
A.
The Print
chosen
The Print is a renowned photography book by Ansel Adams that focuses on the art and technique of photographic printing and darkroom processes.
-
B.
The Paper
The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
-
C.
The Paper
The Paper is a 2000s-era film project that featured dialect coach and actress Cynthia Blaise among its creative contributors.
-
D.
The Inkwell
The Inkwell is a 1994 coming-of-age comedy-drama film set during a family summer vacation on Martha’s Vineyard, known for its exploration of Black middle-class life in the 1970s.
-
E.
Perfect on Paper
Perfect on Paper is a romantic comedy film featuring actor Drew Fuller in a leading role.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6598cc5108190bca2a47c9f8ef70f |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:52 p.m.