Triple
T9901030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ypres 1917 |
E182281
|
entity |
| Predicate | tookPlaceInTerrain |
P56549
|
FINISHED |
| Object | low-lying Flanders plain |
—
|
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: low-lying Flanders plain | Statement: [Ypres 1917, tookPlaceInTerrain, low-lying Flanders plain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookPlaceInTerrain Context triple: [Ypres 1917, tookPlaceInTerrain, low-lying Flanders plain]
-
A.
locatedOnTerrain
chosen
Indicates that one entity is physically situated on or atop a particular terrain surface.
-
B.
terrainIncludes
Indicates that a specified terrain area contains or encompasses another geographic or environmental feature within its boundaries.
-
C.
terrainFeature
Indicates a relationship where one entity is a natural or constructed landform or surface characteristic associated with a given location or area.
-
D.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
-
E.
hasTerrainPark
Indicates that a location or facility includes a designated terrain park area for activities such as skiing or snowboarding.
- 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_69ca82876f8081909cf75df0f99bb13f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4e221448190b536742d1269f9d7 |
completed | April 2, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69cd1d8c584081908b73de75eb18e438 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:40 p.m.