Triple
T2687045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgetown Waterfront |
E57507
|
entity |
| Predicate | localPopularity |
P1755
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Georgetown Waterfront, localPopularity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localPopularity Context triple: [Georgetown Waterfront, localPopularity, high]
-
A.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
B.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
-
C.
popularity
chosen
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
D.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
-
E.
primaryRegionOfPopularity
Indicates the geographic region where something is most widely used, favored, or popular compared to other regions.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9f080108190ab662a3a064cb5a9 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.