Triple
T32559826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dice (HBO stand-up special) |
E832190
|
entity |
| Predicate | containsContentCharacteristic |
P99469
|
FINISHED |
| Object | profanity-laced material |
—
|
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: profanity-laced material | Statement: [Dice (HBO stand-up special), containsContentCharacteristic, profanity-laced material]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsContentCharacteristic Context triple: [Dice (HBO stand-up special), containsContentCharacteristic, profanity-laced material]
-
A.
containsCharacter
Indicates that one entity includes a specific character as part of its content or composition.
-
B.
hasChertContent
Indicates that an entity contains or is characterized by a certain amount or proportion of chert.
-
C.
containsCharacterAction
Indicates that an entity includes or features an action performed by a character within it.
-
D.
contentCharacterization
Indicates that one entity characterizes, describes, or classifies the content or informational nature of another entity.
-
E.
subjectHasCharacteristic
chosen
Indicates that a subject possesses, exhibits, or is defined by a particular characteristic or attribute.
- 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_69f34926b9848190ace47d2dd0a0de7c |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ffe01c9d3c819084c256bb3c81c0dc |
completed | May 10, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69ffdfcc78b08190aa4493f13d62a531 |
completed | May 10, 2026, 1:30 a.m. |
Created at: May 1, 2026, 1:03 a.m.