Triple
T13842581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esbly |
E332698
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object | Esbly station |
E726443
|
NE 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: Esbly station | Statement: [Esbly, hasRailwayStation, Esbly station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esbly station Context triple: [Esbly, hasRailwayStation, Esbly station]
-
A.
Elwyn station
Elwyn station is a commuter rail stop in Pennsylvania that serves as a key station on SEPTA’s Media/Wawa Line.
-
B.
Bryn station
Bryn station is a metro station in Oslo, Norway, on the city’s rapid transit network.
-
C.
Ellesmere station
Ellesmere station is a former Toronto subway station on Line 3 Scarborough that served the Scarborough area before the line’s closure.
-
D.
Eythorne station
Eythorne station is a preserved heritage railway station in Kent, England, serving as part of the East Kent Railway tourist line.
-
E.
Beynes station
chosen
Beynes station is a suburban railway station in Beynes, France, served by Paris’ Transilien commuter network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02afce788190a74dce4e6a3569fa |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b8f87c188190b90faf7678cb9ad4 |
completed | May 3, 2026, 9:07 p.m. |
Created at: April 9, 2026, 10:13 p.m.