Triple
T19447284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remiremont |
E486511
|
entity |
| Predicate | distanceToNancyKilometres |
P135922
|
FINISHED |
| Object | about 90 |
—
|
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 90 | Statement: [Remiremont, distanceToNancyKilometres, about 90]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToNancyKilometres Context triple: [Remiremont, distanceToNancyKilometres, about 90]
-
A.
distanceToNiceKilometers
Indicates the physical distance, measured in kilometers, between an entity and the city of Nice.
-
B.
distanceFromNiceByRoad_km
Indicates the length of the road route, in kilometers, from the city of Nice to the given location.
-
C.
distanceFromNice
Indicates the spatial distance between an entity and the location referred to as Nice.
-
D.
distanceFromLyon
Indicates the spatial distance between a given entity and the city of Lyon.
-
E.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338b25d88190bc137a411576c73f |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:38 p.m.