Triple
T13181811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western Croatia |
E313747
|
entity |
| Predicate | hasHinterland |
P52232
|
FINISHED |
| Object | mountainous hinterland |
—
|
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: mountainous hinterland | Statement: [Western Croatia, hasHinterland, mountainous hinterland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHinterland Context triple: [Western Croatia, hasHinterland, mountainous hinterland]
-
A.
hasRuralHinterland
chosen
Indicates that a place or urban area is associated with and served by a surrounding rural region that supports it economically, socially, or functionally.
-
B.
hasInlandCity
Indicates that one entity has, contains, or is associated with a city located inland (away from the coast or major bodies of water).
-
C.
hasInlandArea
Indicates that an entity possesses a portion of its territory or surface that is located away from coastal or shoreline areas.
-
D.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
-
E.
hasLandComponent
Indicates that something includes, consists of, or is associated with a land-based part or portion as one of its components.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:15 p.m.