Triple
T3898089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U2 (Nuremberg U-Bahn) |
E90419
|
entity |
| Predicate | networkMapDisplay |
P15053
|
FINISHED |
| Object | Nuremberg U-Bahn network map |
—
|
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: Nuremberg U-Bahn network map | Statement: [U2 (Nuremberg U-Bahn), networkMapDisplay, Nuremberg U-Bahn network map]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkMapDisplay Context triple: [U2 (Nuremberg U-Bahn), networkMapDisplay, Nuremberg U-Bahn network map]
-
A.
networkMapName
Indicates the designated name or label assigned to a particular network map within a system or context.
-
B.
networkModel
Indicates a relationship where an entity is represented or organized according to a specific network-based structure or framework.
-
C.
originalNetworkDepicted
chosen
Indicates that one entity visually represents or portrays the original network associated with another entity.
-
D.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
E.
networkSection
Indicates that one entity represents a specific section, segment, or subdivision within a larger network structure.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75b5b808190a348a31b1325d3d0 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:21 p.m.