Triple
T5790689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Høyblokka |
E128383
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Grubbegata |
E518507
|
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: Grubbegata | Statement: [Høyblokka, locatedNear, Grubbegata]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grubbegata Context triple: [Høyblokka, locatedNear, Grubbegata]
-
A.
Grubbegata
chosen
Grubbegata is a street in central Oslo, Norway, known for running through the area that houses key government buildings and institutions.
-
B.
Blackeberg
Blackeberg is a suburban district in western Stockholm, Sweden, best known internationally as the bleak, wintry backdrop of the Swedish vampire novel and film "Let the Right One In."
-
C.
Thorildsplan
Thorildsplan is a Stockholm metro station located on the island district of Kungsholmen in central Stockholm, Sweden.
-
D.
Hjulsta
Hjulsta is a suburb in northwestern Stockholm, Sweden, known for being the terminus of one of the Stockholm metro lines.
-
E.
Enebyberg
Enebyberg is a residential suburban area in the northern part of the Stockholm urban region in Sweden.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a56c73c81908a1c72c86e474b54 |
completed | March 22, 2026, 5:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c09820f5c08190811e848eb44ce5b9 |
completed | March 23, 2026, 1:32 a.m. |
Created at: March 22, 2026, 3:51 p.m.