Triple
T2766806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic Ocean proper by Martha's Vineyard |
E61357
|
entity |
| Predicate | hasPrimaryLanguageOfNearbyShore |
P43023
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Atlantic Ocean proper by Martha's Vineyard, hasPrimaryLanguageOfNearbyShore, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfNearbyShore Context triple: [Atlantic Ocean proper by Martha's Vineyard, hasPrimaryLanguageOfNearbyShore, English]
-
A.
hasNearbyCoast
Indicates that one location is situated close to a coastline or seashore.
-
B.
hasShoreOn
Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
-
C.
hasShorelineCountry
Indicates that a country possesses a coastline or land boundary directly adjacent to a particular body of water or coastal region.
-
D.
hasCityOnShore
Indicates that a city is located on or directly adjacent to the shore of a body of water.
-
E.
hasEstuaryNear
Indicates that the estuary of a water body is located in close proximity to a specified place or feature.
- F. None of above. chosen
Provenance (4 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abddcc348081908b5f760899389d4f |
completed | March 7, 2026, 8:11 a.m. |
Created at: March 6, 2026, 9:57 p.m.