Triple
T23358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha's Vineyard |
E463
|
entity |
| Predicate | popularWith |
P729
|
FINISHED |
| Object | vacationers from the northeastern United States |
—
|
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: vacationers from the northeastern United States | Statement: [Martha's Vineyard, popularWith, vacationers from the northeastern United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: popularWith Context triple: [Martha's Vineyard, popularWith, vacationers from the northeastern United States]
-
A.
isPopularWith
chosen
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
B.
popularInCentury
Indicates that something was widely liked, influential, or commonly recognized during a specified century.
-
C.
popularSeason
Indicates that a particular season is widely liked, favored, or frequently chosen by many people.
-
D.
popularVoteWinner
Indicates that the subject is the candidate who received the highest number of individual votes cast by the electorate in an election.
-
E.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.