Triple
T18645465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterland Ballroom |
E455793
|
entity |
| Predicate | openedAsWinterland |
P132857
|
FINISHED |
| Object | 1928 |
—
|
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: 1928 | Statement: [Winterland Ballroom, openedAsWinterland, 1928]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedAsWinterland Context triple: [Winterland Ballroom, openedAsWinterland, 1928]
-
A.
openedAsSkiArea
Indicates that an entity began operating or was first established specifically as a ski area.
-
B.
hasFrozenInWinter
Indicates that something becomes or has become frozen during the winter season.
-
C.
firstWinterEdition
Indicates that the subject entity is the first instance of something to occur in a winter edition or winter season context.
-
D.
hasWinterActivitySeason
Indicates that an entity’s primary period for engaging in a particular activity occurs during the winter season.
-
E.
openedAsResort
Indicates that something began operating or was first established in the capacity of a resort.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5500d69648190800da65de0c191b8 |
completed | April 19, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484121cd48190bf583b4c94636a30 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:47 a.m.