Triple
T574348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeeland |
E13728
|
entity |
| Predicate | hasLandReclamation |
P16193
|
FINISHED |
| Object | polders |
—
|
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: polders | Statement: [Zeeland, hasLandReclamation, polders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandReclamation Context triple: [Zeeland, hasLandReclamation, polders]
-
A.
hasEnvironmentalImpactOn
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
environmentalRemediation
Indicates actions or processes undertaken to remove, reduce, or neutralize pollution or environmental damage in order to restore a site or ecosystem to a safer or more natural condition.
-
C.
hasLandings
Indicates that an entity has one or more associated landing events or landing locations.
-
D.
hasLandCoverage
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
E.
hasRestorationActivities
Indicates that an entity carries out, is involved in, or is associated with actions aimed at restoring or rehabilitating another entity or resource.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b4c23548190a3b883239c7c78c8 |
completed | March 1, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_69a494c4969c819080375d08f9eec50c |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498dd579081908e02368a4c5efc8c |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:33 p.m.