Triple
T11851972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M’lang |
E281928
|
entity |
| Predicate | hasLandlockedStatus |
P101856
|
FINISHED |
| Object | landlocked |
—
|
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: landlocked | Statement: [M’lang, hasLandlockedStatus, landlocked]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandlockedStatus Context triple: [M’lang, hasLandlockedStatus, landlocked]
-
A.
isInLandlockedCountry
Indicates that the entity is located within a country that has no direct access to the ocean or sea.
-
B.
isLandlockedByRoad
Indicates that a place has no direct road access to the broader road network except through another surrounding or enclosing region.
-
C.
isLandlockedWithinIsland
Indicates that an entity has no direct access to the open sea and is entirely surrounded by land that itself is part of an island.
-
D.
isInLandlockedCounty
Indicates that an entity is located within a county that has no direct access to the ocean or sea.
-
E.
isOnlyLandlockedMunicipalityIn
Indicates that a municipality is the sole municipality within a given region or jurisdiction that has no direct access to the sea or ocean (i.e., is landlocked).
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a696ee548190800d56c64c339b10 |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.