Triple
T37639045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | provinces of the Low Countries |
E936565
|
entity |
| Predicate | roughlyCorrespondTo |
P25442
|
FINISHED |
| Object | Belgium |
—
|
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: Belgium | Statement: [provinces of the Low Countries, roughlyCorrespondTo, Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roughlyCorrespondTo Context triple: [provinces of the Low Countries, roughlyCorrespondTo, Belgium]
-
A.
correspondsWith
Indicates that two entities are in mutual alignment or agreement, such that one matches, parallels, or is equivalent to the other in a specified respect.
-
B.
partiallyCorrespondsTo
chosen
Indicates that one entity matches or aligns with another entity only in some aspects, segments, or components, rather than fully or exactly.
-
C.
representsApproximately
Indicates that one entity serves as an inexact or close-but-not-exact representation or value of another entity.
-
D.
alignedApproximately
Indicates that two or more entities are positioned or oriented in roughly the same direction or arrangement, allowing for minor deviations or imprecision.
-
E.
containsApproximately
Indicates that one entity holds or includes another entity in a quantity or proportion that is close to, but not exactly, a specified amount.
- 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_69f76ed31d8881908405da6c6d2f0463 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaa1321b48190af92a3e7ec24ec5b |
completed | May 6, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69fba8860f98819080b7bab05837b974 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:18 p.m.