Triple
T14601306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catacombs of Paris |
E342710
|
entity |
| Predicate | lengthOfTunnels |
P114992
|
FINISHED |
| Object | over 300 kilometers |
—
|
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: over 300 kilometers | Statement: [Catacombs of Paris, lengthOfTunnels, over 300 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lengthOfTunnels Context triple: [Catacombs of Paris, lengthOfTunnels, over 300 kilometers]
-
A.
numberOfMajorTunnels
Indicates the count of primary or significant tunnels associated with an entity.
-
B.
tunnels
Indicates that one entity passes through, under, or within another entity via a tunnel-like passage or structure.
-
C.
numberOfTunnels
Indicates the quantity of tunnels associated with or passing through a given entity or location.
-
D.
hasRailwayTunnel
Indicates that one entity contains, includes, or is connected by a railway tunnel associated with the other entity.
-
E.
isOneOfLongestNavigableCanalTunnelsIn
Indicates that something ranks among the longest canal tunnels that can be navigated within a specified place or region.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
| PDg | Predicate description generation | batch_69de716c17cc8190aeb85296abee85a7 |
completed | April 14, 2026, 4:55 p.m. |
Created at: April 10, 2026, 1:25 a.m.