Triple
T35177185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E46 |
E1015738
|
entity |
| Predicate | followsMotorway |
P56524
|
FINISHED |
| Object |
French A13 motorway
The French A13 motorway is a major toll highway in northern France that connects Paris to Normandy, including the city of Caen.
|
E2129696
|
NE FINISHED |
How this triple was built (3 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: French A13 motorway | Statement: [European route E46, followsMotorway, French A13 motorway]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: French A13 motorway Triple: [European route E46, followsMotorway, French A13 motorway]
Generated description
The French A13 motorway is a major toll highway in northern France that connects Paris to Normandy, including the city of Caen.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsMotorway Context triple: [European route E46, followsMotorway, French A13 motorway]
-
A.
followsHighway
chosen
Indicates that one entity’s path or route runs along, parallels, or adheres closely to the course of a specified highway.
-
B.
motorwayServedBy
Indicates that a motorway is connected to or accessed by a particular service facility, route, or transport service.
-
C.
isMotorwayIn
Indicates that a motorway is located within or passes through a specified geographic area or administrative region.
-
D.
nearestMotorway
Indicates that one entity is the motorway that is geographically closest to the other entity.
-
E.
motorwayConnectionWith
Indicates that two locations are directly connected by a motorway, allowing vehicular travel between them via that road.
- F. None of above.
Provenance (6 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a37fb1757bc81909365f66fb30f2380 |
completed | June 21, 2026, 2:54 p.m. |
| NEDg | Description generation | batch_6a37fbeeeafc81908120d6489582b61a |
completed | June 21, 2026, 2:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a37fc86db2481909015f6fe63315f08 |
completed | June 21, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: May 3, 2026, 4:02 p.m.