Triple
T23399454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hammarby IF DFF |
E559461
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Hammarby |
—
|
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: Hammarby | Statement: [Hammarby IF DFF, shortName, Hammarby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hammarby Context triple: [Hammarby IF DFF, shortName, Hammarby]
-
A.
Hammarby IF
chosen
Hammarby IF is a Swedish sports club from Stockholm best known for its passionate fan base and prominent football team competing in the country’s top divisions.
-
B.
Djurgården
Djurgården is a central Stockholm island known for its parks, museums, and major attractions like the Vasa Museum and Skansen.
-
C.
Landskrona
Landskrona is a coastal town in southern Sweden known for its historic fortifications, harbor, and role in regional conflicts between Denmark and Sweden.
-
D.
Bromma
Bromma is a suburban district in western Stockholm, Sweden, known for its residential areas, green spaces, and the city’s secondary airport.
-
E.
Hammarby Sjöstad
Hammarby Sjöstad is a modern, sustainably planned waterfront district in Stockholm known for its eco-friendly architecture and urban design.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e24549610c8190a069d6411ce5f661 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a4ddcb9481909881c77458c59c83 |
completed | April 29, 2026, 6:27 a.m. |
Created at: April 17, 2026, 5:37 p.m.