Triple
T31030413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chauny |
E790705
|
entity |
| Predicate | departmentCapitalDistanceKm |
P171120
|
FINISHED |
| Object | about 35 km from Laon |
—
|
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 35 km from Laon | Statement: [Chauny, departmentCapitalDistanceKm, about 35 km from Laon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: departmentCapitalDistanceKm Context triple: [Chauny, departmentCapitalDistanceKm, about 35 km from Laon]
-
A.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
departmentCapitalOf
Indicates that a location serves as the administrative capital of a specified department (an administrative division).
-
C.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
D.
distanceToProvinceCapital_km
Indicates the distance, measured in kilometers, between a given location and the capital city of its province.
-
E.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
- 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_69f224c97a788190b5da1ead6038a74e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f698ad83a08190a6834056ccc3e3a4 |
completed | May 3, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f697e92e2c8190bed50d5ba0981b64 |
completed | May 3, 2026, 12:33 a.m. |
Created at: April 29, 2026, 8:59 p.m.