Triple
T4227724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dourdan station |
E94498
|
entity |
| Predicate | distanceFromParisAusterlitz |
P55435
|
FINISHED |
| Object | approximately 50 km |
—
|
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: approximately 50 km | Statement: [Dourdan station, distanceFromParisAusterlitz, approximately 50 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromParisAusterlitz Context triple: [Dourdan station, distanceFromParisAusterlitz, approximately 50 km]
-
A.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
B.
distanceToMetzKilometers
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Metz.
-
C.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
D.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
E.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e5003008190834726e46df3ee9b |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e4ace648190acf911853d4fcf86 |
completed | March 12, 2026, 11:37 p.m. |
Created at: March 12, 2026, 11:04 p.m.