Triple
T38559237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 12 |
E928031
|
entity |
| Predicate | hasOriginalScoreFor |
P199653
|
FINISHED |
| Object | Revolutionary Road (2008 film) |
—
|
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: Revolutionary Road (2008 film) | Statement: [Route 12, hasOriginalScoreFor, Revolutionary Road (2008 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginalScoreFor Context triple: [Route 12, hasOriginalScoreFor, Revolutionary Road (2008 film)]
-
A.
hasOriginalScoreAlbum
Indicates that an entity is associated with a specific album containing its original musical score.
-
B.
hasOriginalScoreStyle
Indicates that an entity’s original score is composed or arranged in a particular musical style or genre.
-
C.
hasScoreBy
Indicates that one entity possesses or is associated with a score that was assigned, produced, or determined by another entity.
-
D.
scoringInOriginalUse
Indicates that an entity is performing a scoring action within its initial or primary context of use, rather than in a derived or subsequent context.
-
E.
hasScoreRecord
Indicates that an entity is associated with a specific score entry or scoring record.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff49f888348190b9c55afa73b99e6a |
completed | May 9, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69ff49614ef88190ac70b034c55ad738 |
completed | May 9, 2026, 2:49 p.m. |
| PDg | Predicate description generation | batch_69ff49f7db2c819094d488d13985334c |
completed | May 9, 2026, 2:51 p.m. |
Created at: May 3, 2026, 4:32 p.m.