Triple
T13248410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A-road |
E315463
|
entity |
| Predicate | mapsSymbol |
P19295
|
FINISHED |
| Object | green or red lines on many road atlases |
—
|
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: green or red lines on many road atlases | Statement: [A-road, mapsSymbol, green or red lines on many road atlases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapsSymbol Context triple: [A-road, mapsSymbol, green or red lines on many road atlases]
-
A.
mapSymbol
chosen
Indicates a correspondence where one symbol is used to represent, stand for, or denote another element within a mapping or representation system.
-
B.
mapsDepict
Indicates that maps visually represent or illustrate the geographic features, locations, or spatial relationships of something.
-
C.
mapLabel
Indicates that a label or name is assigned to a map or mapped entity for identification or display.
-
D.
mapsFrom
Indicates that one entity is derived, transformed, or constructed based on data, structure, or content originating from another entity.
-
E.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d9e7ea881908abc4b3a54896692 |
completed | April 10, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:24 p.m.