Triple
T24837030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts–Rhode Island border |
E621505
|
entity |
| Predicate | liesNearBodyOfWater |
P49291
|
FINISHED |
| Object | Mount Hope Bay |
—
|
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: Mount Hope Bay | Statement: [Massachusetts–Rhode Island border, liesNearBodyOfWater, Mount Hope Bay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: liesNearBodyOfWater Context triple: [Massachusetts–Rhode Island border, liesNearBodyOfWater, Mount Hope Bay]
-
A.
locatedInBodyOfWater
Indicates that an entity is situated within or on the surface of a specific body of water.
-
B.
adjacentToBodyOfWater
Indicates that one entity is directly next to or bordering a body of water, such as a lake, river, or ocean.
-
C.
hasNearbyWater
chosen
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
D.
involvesBodyOfWater
Indicates that the relationship or event includes, affects, or takes place in connection with a body of water such as a sea, lake, river, or ocean.
-
E.
hasBodyOfWaterType
Indicates that a body of water is classified as being of a particular type or category (such as lake, river, ocean, etc.).
- 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_69f44a417a58819081777e18dda149fd |
completed | May 1, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69f442b8479c8190a7c8e416ac9e28a0 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 5:18 a.m.