Triple
T36332328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg Airport station |
E894682
|
entity |
| Predicate | adjacentStationOnLineS1 |
P192461
|
FINISHED |
| Object | Ohlsdorf station |
—
|
NE NERFINISHED |
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: Ohlsdorf station | Statement: [Hamburg Airport station, adjacentStationOnLineS1, Ohlsdorf station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentStationOnLineS1 Context triple: [Hamburg Airport station, adjacentStationOnLineS1, Ohlsdorf station]
-
A.
adjacentStationOnLine
Indicates that one station is directly next to another station along the same transit line, with no other station in between.
-
B.
adjacentStationOnLineL
Indicates that one station is directly next to another station along the same transit line L, with no other stations in between.
-
C.
adjacentStationOnLineD
Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
-
D.
adjacentStationOnLineU1
Indicates that two stations are directly next to each other as consecutive stops on subway line U1.
-
E.
adjacentStationOnLineU2
Indicates that two stations are directly next to each other on subway line U2, with no other station in between.
- 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_69f76e4dcf088190a6c3216c209cab52 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
| PDg | Predicate description generation | batch_69fd0b92150881909b1166fe6d09aa19 |
completed | May 7, 2026, 10 p.m. |
Created at: May 3, 2026, 4:09 p.m.