Triple
T3088663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | For the First Time in Forever: A Frozen Sing-Along Celebration |
E64433
|
entity |
| Predicate | featuresSnowEffects |
P45836
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [For the First Time in Forever: A Frozen Sing-Along Celebration, featuresSnowEffects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSnowEffects Context triple: [For the First Time in Forever: A Frozen Sing-Along Celebration, featuresSnowEffects, yes]
-
A.
hasSnowfall
Indicates that a location or area experiences or contains snowfall.
-
B.
snowmaking
Indicates the artificial production of snow, typically by machines, for use in places like ski slopes or winter recreation areas.
-
C.
hasSnowAtHighElevations
Indicates that snow is present in areas located at higher elevations within a given region or context.
-
D.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
E.
hasNightSkiing
Indicates that a location or facility offers skiing activities that take place during nighttime under artificial lighting.
- 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20b99a4819090c3d3e08ed556ad |
completed | March 8, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.