Triple
T8281061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lange Niezel |
E193671
|
entity |
| Predicate | hasNearby |
P350
|
FINISHED |
| Object | Damrak |
E74635
|
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: Damrak | Statement: [Lange Niezel, hasNearby, Damrak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Damrak Context triple: [Lange Niezel, hasNearby, Damrak]
-
A.
Damrak
chosen
Damrak is a central street and canal in Amsterdam that runs from Amsterdam Centraal Station toward Dam Square, forming one of the city’s main tourist and commercial arteries.
-
B.
Bazarak
Bazarak is a small town in northeastern Afghanistan that serves as the administrative and political center of the strategically significant Panjshir region.
-
C.
Gouderak
Gouderak is a small village in the Dutch province of South Holland, situated along the Hollandse IJssel river.
-
D.
Samalkha
Samalkha is a town in the northern Indian state of Haryana, known for its industrial activity and location along major transport routes.
-
E.
Dombay
Dombay is a mountain resort settlement in the North Caucasus of Russia, known for its alpine scenery, skiing, and hiking opportunities.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ee66e48190af7058b14f3daac9 |
completed | March 31, 2026, 7:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd6877b8e481908ec1e0b91a5276f6 |
completed | April 1, 2026, 6:48 p.m. |
Created at: March 30, 2026, 5:51 p.m.