Triple
T23649754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cenabum – Orléans |
E584134
|
entity |
| Predicate | distanceFromParisApproximate |
P10703
|
FINISHED |
| Object | about 120 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: about 120 km | Statement: [Cenabum – Orléans, distanceFromParisApproximate, about 120 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromParisApproximate Context triple: [Cenabum – Orléans, distanceFromParisApproximate, about 120 km]
-
A.
distanceFromParisCenter
chosen
Indicates the measured distance between a given location and the central point of Paris.
-
B.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
C.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
D.
distanceFromLyon
Indicates the spatial distance between a given entity and the city of Lyon.
-
E.
distanceFromParisGareDeLyon
Indicates the distance between an entity and Paris Gare de Lyon 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.