Triple
T24837053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts–Rhode Island border |
E621505
|
entity |
| Predicate | hasNeighboringStateToSouth |
P117551
|
FINISHED |
| Object | Rhode Island |
—
|
NE NERFINISHED |
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: Rhode Island | Statement: [Massachusetts–Rhode Island border, hasNeighboringStateToSouth, Rhode Island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighboringStateToSouth Context triple: [Massachusetts–Rhode Island border, hasNeighboringStateToSouth, Rhode Island]
-
A.
hasNeighboringStateToWest
Indicates that one state is geographically located directly to the west of another state, sharing a common border.
-
B.
hasNeighboringCountryToNorth
Indicates that one country is directly adjacent to and located south of another country, which lies to its north.
-
C.
hasNeighbouringState
Indicates that one state shares a common border or is directly adjacent geographically to another state.
-
D.
hasSouthBorder
chosen
Indicates that one entity shares its southern boundary or border with another entity.
-
E.
isInUnitedStatesSouth
Indicates that something is located within the southern region of the United States.
- 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_69e2fac185d48190a0a6073ad1f6b792 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 5:18 a.m.