Triple
T30575949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Slater as Daniel Molloy |
E778244
|
entity |
| Predicate | mediumUsedToRecord |
P165538
|
FINISHED |
| Object | audio cassette tapes |
—
|
LITERAL 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: audio cassette tapes | Statement: [Christian Slater as Daniel Molloy, mediumUsedToRecord, audio cassette tapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumUsedToRecord Context triple: [Christian Slater as Daniel Molloy, mediumUsedToRecord, audio cassette tapes]
-
A.
mediumOfRecord
chosen
Indicates the primary medium or format through which an event, work, or information is officially documented or recorded.
-
B.
mediumOfProduction
Indicates the method, material, or technology used to create or produce something.
-
C.
usedMedium
Indicates that an action or communication was carried out through a particular medium or channel.
-
D.
mediumDepictedIn
Indicates that a particular medium or material is represented, shown, or referenced within another work or depiction.
-
E.
mediumOfOperation
Indicates the method, channel, or medium through which an action, process, or interaction is carried out or operates.
- F. None of above.
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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6893cedbc8190af12752ccae5e062 |
completed | May 2, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f67e42d6688190b60e91d2c388c555 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:22 p.m.