Triple
T18762669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisa Cholodenko |
E458810
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Transparent |
—
|
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: Transparent | Statement: [Lisa Cholodenko, directed, Transparent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Transparent Context triple: [Lisa Cholodenko, directed, Transparent]
-
A.
Transparent
chosen
Transparent is a critically acclaimed American television dramedy series that explores themes of gender identity, family dynamics, and personal transformation within a Los Angeles Jewish family.
-
B.
See-Through
"See-Through" is a song by the American rock band Long Division.
-
C.
Clear
Clear is a central Scientology attainment state in which a person is believed to be free from the influence of the reactive mind and its stored traumas.
-
D.
CLARITY
CLARITY is a tissue-clearing technique that renders biological tissues transparent while preserving their molecular and structural integrity for high-resolution imaging and analysis.
-
E.
Invisibly
Invisibly is a data and advertising technology company that aims to give consumers control over their personal data and how it is monetized.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d80a954819083946dafc0c7af05 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 10, 2026, 11:52 a.m.