Triple
T12842880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M53 |
E307096
|
entity |
| Predicate | hasJunction |
P1018
|
FINISHED |
| Object |
Junction 3
Junction 3 is a major motorway interchange on the M53 in northwest England, connecting local routes to the wider regional road network.
|
E1006023
|
NE FINISHED |
How this triple was built (4 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: Junction 3 | Statement: [M53, hasJunction, Junction 3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Junction 3 Context triple: [M53, hasJunction, Junction 3]
-
A.
Junction 3
Junction 3 is a numbered exit on England’s M66 motorway serving local connections in the Greater Manchester area.
-
B.
Junction 2
Junction 2 is a numbered interchange on the M66 motorway in Greater Manchester, England, providing access between the motorway and local road networks.
-
C.
Junction 5
Junction 5 is a numbered interchange on England’s M20 motorway, providing access between the motorway and the surrounding local road network.
-
D.
Junction 5
Junction 5 is a numbered exit on England’s M58 motorway, providing access between the motorway and the surrounding local road network.
-
E.
Junction 1
Junction 1 is a motorway interchange on the M20 in southeast England, providing access between the M20 and local roads near the London orbital route.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Junction 3 Triple: [M53, hasJunction, Junction 3]
Generated description
Junction 3 is a major motorway interchange on the M53 in northwest England, connecting local routes to the wider regional road network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Junction 3 Target entity description: Junction 3 is a major motorway interchange on the M53 in northwest England, connecting local routes to the wider regional road network.
-
A.
Junction 3
Junction 3 is a numbered exit on England’s M66 motorway serving local connections in the Greater Manchester area.
-
B.
Junction 2
Junction 2 is a numbered interchange on the M66 motorway in Greater Manchester, England, providing access between the motorway and local road networks.
-
C.
Junction 5
Junction 5 is a numbered exit on England’s M58 motorway, providing access between the motorway and the surrounding local road network.
-
D.
Junction 5
Junction 5 is a numbered interchange on England’s M20 motorway, providing access between the motorway and the surrounding local road network.
-
E.
Junction 1
Junction 1 is a motorway interchange on the M20 in southeast England, providing access between the M20 and local roads near the London orbital route.
- F. None of above. chosen
Provenance (5 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff2ab60819085561a3120189985 |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b9dc1e48190993430956e0fcfdc |
completed | May 3, 2026, 12:49 a.m. |
| NEDg | Description generation | batch_69f69ca6358c8190bb076249864f81a8 |
completed | May 3, 2026, 12:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69dc8b86c81908557fa8538e942de |
completed | May 3, 2026, 12:58 a.m. |
Created at: April 9, 2026, 5:35 p.m.