Triple
T25668507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plateau de Châtillon |
E643593
|
entity |
| Predicate | elevationRelativeToParisCenter |
P102577
|
FINISHED |
| Object | higher |
—
|
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: higher | Statement: [Plateau de Châtillon, elevationRelativeToParisCenter, higher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: elevationRelativeToParisCenter Context triple: [Plateau de Châtillon, elevationRelativeToParisCenter, higher]
-
A.
elevationRelativeToParis
chosen
Indicates the relative elevation difference between a given location and Paris, specifying how much higher or lower it is in altitude.
-
B.
elevationRelativeToDamascus
Indicates the relative elevation difference between a given location and the city of Damascus, specifying how much higher or lower the location is compared to Damascus.
-
C.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
D.
rankingInFranceByHeight
Indicates the relative order of entities in France based on their height, from tallest to shortest or vice versa.
-
E.
hasElevationRelativeToSeaLevel
Indicates the elevation or height of an entity measured relative to mean sea level.
- 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_69e77e7e45648190a068ed3faa8016ea |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 7:09 p.m.