Triple
T25590181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin–Stettin railway |
E641500
|
entity |
| Predicate | hasEndpointCityCurrentName |
P26386
|
FINISHED |
| Object | Szczecin |
—
|
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: Szczecin | Statement: [Berlin–Stettin railway, hasEndpointCityCurrentName, Szczecin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndpointCityCurrentName Context triple: [Berlin–Stettin railway, hasEndpointCityCurrentName, Szczecin]
-
A.
hasEndpointCity
chosen
Indicates that a route, connection, or path terminates at a particular city as one of its endpoints.
-
B.
hasEndpointAirport
Indicates that something, such as a route or flight, has a specific airport as one of its terminal endpoints.
-
C.
endPointCityCountry
Indicates that a specific city and country serve as the ending location for a given route, trip, or connection.
-
D.
hasCurrentCoreCityName
Indicates that an entity is associated with its present or officially recognized core city name.
-
E.
currentCityName
Indicates the name of the city where the entity is currently located.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 21, 2026, 4:19 p.m.