Triple
T23649621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cenabum |
E584131
|
entity |
| Predicate | regionRelativeToParis |
P45843
|
FINISHED |
| Object | southwest of Paris |
—
|
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: southwest of Paris | Statement: [Cenabum, regionRelativeToParis, southwest of Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionRelativeToParis Context triple: [Cenabum, regionRelativeToParis, southwest of Paris]
-
A.
elevationRelativeToParis
Indicates the relative elevation difference between a given location and Paris, specifying how much higher or lower it is in altitude.
-
B.
locatedInMetropolitanFrance
Indicates that the subject is geographically situated within the territory of metropolitan (continental) France.
-
C.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
D.
directionFromParis
chosen
Indicates the cardinal or relative compass direction of an entity as measured from Paris toward that entity.
-
E.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
- 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2885b408190a43dfed93309a4d6 |
completed | April 29, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:49 p.m.