Triple
T17136834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muzeum station |
E415859
|
entity |
| Predicate | lineAStationDepth |
P126245
|
FINISHED |
| Object | deep-level |
—
|
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: deep-level | Statement: [Muzeum station, lineAStationDepth, deep-level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineAStationDepth Context triple: [Muzeum station, lineAStationDepth, deep-level]
-
A.
deepestStation
Indicates that one station in a network or system is located at a greater depth (e.g., below ground or sea level) than all other stations.
-
B.
oneOfDeepestStationsIn
Indicates that a station is among the deepest stations located within a specified area or system.
-
C.
stationNumber
Indicates the specific station identifier or code assigned to an entity within a system or network.
-
D.
rankByDepthInNYCSubway
Indicates the relative ordering of entities based on how deep they are located within the New York City subway system.
-
E.
railLineTerminus
Indicates that a rail line ends or terminates at the specified location or station.
- F. None of above. chosen
Provenance (4 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d0628081908e0160290041fe89 |
completed | April 18, 2026, 9:08 p.m. |
| PD | Predicate disambiguation | batch_69e3830192ac819091344a9e5a36c8c9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:36 a.m.