Triple
T4668226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Anne Revival |
E102898
|
entity |
| Predicate | hadPeakPopularity |
P55472
|
FINISHED |
| Object | 1880s |
—
|
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: 1880s | Statement: [Queen Anne Revival, hadPeakPopularity, 1880s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadPeakPopularity Context triple: [Queen Anne Revival, hadPeakPopularity, 1880s]
-
A.
hadPeakInfluencePeriod
chosen
Indicates the time span during which an entity exerted its greatest or most significant influence.
-
B.
hasEnduringPopularityOn
Indicates that something continues to be widely liked, used, or appreciated on a particular platform, medium, or context over an extended period of time.
-
C.
hasPeak
Indicates that something possesses or contains a highest point, summit, or maximum value.
-
D.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
E.
hasPopularityReason
Indicates that there is a specific reason or factor explaining why something is popular.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd655aceb081908100ffc0498fe183 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6215864c8190b50ba0f63ba87d0c |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:15 p.m.