Triple
T1092733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zurich Hauptbahnhof |
E24201
|
entity |
| Predicate | UICCode |
P5624
|
FINISHED |
| Object | 8503000 |
—
|
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: 8503000 | Statement: [Zurich Hauptbahnhof, UICCode, 8503000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UICCode Context triple: [Zurich Hauptbahnhof, UICCode, 8503000]
-
A.
UICClassification
chosen
Indicates the standardized classification or coding assigned to an entity according to the UIC (International Union of Railways) system.
-
B.
universityAbbreviation
Indicates that one term is the standard shortened or abbreviated form of the name of a university.
-
C.
FIPSCode
Indicates the standardized Federal Information Processing Standards (FIPS) code assigned to identify a specific geographic or administrative entity.
-
D.
universityLocatedIn
Indicates that a university is situated within or associated with a specific geographic location or administrative region.
-
E.
cityOfInstitution
Indicates the city in which an institution is located or based.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99bd06c8190bce1d77b0337b07c |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.