Triple
T7271855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constantine tramway |
E161125
|
entity |
| Predicate | terrainServed |
P5378
|
FINISHED |
| Object | hilly urban landscape |
—
|
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: hilly urban landscape | Statement: [Constantine tramway, terrainServed, hilly urban landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrainServed Context triple: [Constantine tramway, terrainServed, hilly urban landscape]
-
A.
terrainIncludes
Indicates that a specified terrain area contains or encompasses another geographic or environmental feature within its boundaries.
-
B.
terrainFeature
chosen
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
C.
locatedOnTerrain
Indicates that one entity is physically situated on or atop a particular terrain surface.
-
D.
topographyBasedOn
Indicates that the topographical characteristics of one entity are derived from, determined by, or modeled using the topography of another entity.
-
E.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb8a0b4881908ff27c5a75bd4a95 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76a84a081908d4184c55b728e48 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.