Triple
T529658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Singin' in the Rain |
E10996
|
entity |
| Predicate | AFI100PassionsRanking |
P1944
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Singin' in the Rain, AFI100PassionsRanking, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AFI100PassionsRanking Context triple: [Singin' in the Rain, AFI100PassionsRanking, 16]
-
A.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
B.
rankedAs
chosen
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
-
C.
rankedBy
Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
-
D.
popularFilmIndustry
Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
-
E.
mostAwardsFilm
Indicates that a film is the one that has received the highest number of awards within a given set or context.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d4984c8190ac372171b16bb5e4 |
completed | Feb. 28, 2026, 1:47 p.m. |
| PD | Predicate disambiguation | batch_69a2f01ac3ec8190a94a05955532c7fa |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.