Triple
T18099776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Die Hard (film series) |
E433183
|
entity |
| Predicate | ratingRangeUS |
P130423
|
FINISHED |
| Object | R to PG-13 |
—
|
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: R to PG-13 | Statement: [Die Hard (film series), ratingRangeUS, R to PG-13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ratingRangeUS Context triple: [Die Hard (film series), ratingRangeUS, R to PG-13]
-
A.
ratingCategory
Indicates the qualitative classification or level assigned to a rating (e.g., low, medium, high) within an evaluation or scoring system.
-
B.
offersGradeRange
Indicates that an entity provides educational instruction or services spanning a specified range of grade levels.
-
C.
ratingDescription
Indicates the textual explanation or qualitative summary associated with a given rating or score.
-
D.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
E.
rating
Indicates an evaluation relationship where one entity assigns a qualitative or quantitative score or judgment to another entity.
- F. None of above. chosen
Provenance (4 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb521448190b97d2b2aa7e4d7e6 |
completed | April 19, 2026, 1:50 p.m. |
| PD | Predicate disambiguation | batch_69e4330e1f2881908b2506d47c48736b |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:27 a.m.