Triple
T28173863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North America and Africa |
E715534
|
entity |
| Predicate | facingCoastsInclude |
P164096
|
FINISHED |
| Object | eastern coast of North America |
—
|
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: eastern coast of North America | Statement: [North America and Africa, facingCoastsInclude, eastern coast of North America]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facingCoastsInclude Context triple: [North America and Africa, facingCoastsInclude, eastern coast of North America]
-
A.
includesCoastOf
Indicates that one geographic or administrative entity encompasses or contains the coastline of another entity.
-
B.
isPartOfCoastOf
Indicates that one entity forms a segment or component of the coastline belonging to another entity.
-
C.
basedOnCoast
Indicates that something is situated along, adjacent to, or directly influenced by a coastline.
-
D.
hasCoastline
Indicates that a geographic entity is bordered by and directly touches a sea or ocean along part of its boundary.
-
E.
hasCoastOnOtherSide
Indicates that one geographic entity has a coastline located on the opposite side of another referenced geographic feature or boundary.
- 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_69efd6b340f0819095680e15dcdc1830 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6423853ec8190892ecc3e097deeb3 |
completed | May 2, 2026, 6:28 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
| PDg | Predicate description generation | batch_69f63fd4f7448190930c723ba7cfce62 |
completed | May 2, 2026, 6:17 p.m. |
Created at: April 27, 2026, 10:14 p.m.