Triple
T6939158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A1(M) |
E160628
|
entity |
| Predicate | hasJunctionNumberingSystem |
P34119
|
FINISHED |
| Object | A1(M) junction numbers |
—
|
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: A1(M) junction numbers | Statement: [A1(M), hasJunctionNumberingSystem, A1(M) junction numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJunctionNumberingSystem Context triple: [A1(M), hasJunctionNumberingSystem, A1(M) junction numbers]
-
A.
hasJunctionNumbering
Indicates that a road or route is assigned a specific numbering system for its junctions or intersections.
-
B.
hasJunctionNumberingScheme
chosen
Indicates the specific system or method used to assign numbers to junctions within a network (such as roads or railways).
-
C.
hasJunctionNumberingDirection
Indicates the directional scheme used to assign and order junction numbers along a route or network.
-
D.
hasJunctionNumber
Indicates that a road, route, or similar pathway is assigned a specific junction or exit number.
-
E.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
- F. None of above.
Provenance (3 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e0c74fe48190aeaa018631e52ef6 |
completed | March 27, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bd5a388190a57a96d925696ff6 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.