Triple
T8553900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haarlem–Leiden railway |
E202511
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Sassenheim |
E458100
|
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: Sassenheim | Statement: [Haarlem–Leiden railway, serves, Sassenheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sassenheim Context triple: [Haarlem–Leiden railway, serves, Sassenheim]
-
A.
Sassenheim
chosen
Sassenheim is a town in the Dutch province of South Holland, known historically for its bulb-growing industry and location within the Duin- en Bollenstreek (Dune and Bulb Region).
-
B.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
C.
Assendelft
Assendelft is a historic village in North Holland, Netherlands, known as one of the country’s oldest settlements and for its association with the painter Pieter Saenredam.
-
D.
Stadshagen
Stadshagen is a residential and commercial district on the island of Kungsholmen in central Stockholm, Sweden.
-
E.
Culemborg
Culemborg is a historic town in the Dutch province of Gelderland, known for its medieval center and role in the early Dutch colonial era.
- 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8894e7c8190bc0ae2ceec473ecb |
completed | March 31, 2026, 3:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4cbacad608190adddd91f13e4113b |
completed | April 19, 2026, 12:33 p.m. |
Created at: March 30, 2026, 6:19 p.m.