Triple
T5707070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lillestrøm SK |
E125809
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | LSK |
E539248
|
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: LSK | Statement: [Lillestrøm SK, shortName, LSK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LSK Context triple: [Lillestrøm SK, shortName, LSK]
-
A.
LSK
chosen
LSK is a common abbreviation for Lillestrøm SK, a Norwegian football club known for competing in the country’s top divisions and having a strong local fan base.
-
B.
BSK
BSK is the National Rail station code for Basingstoke railway station in Hampshire, England.
-
C.
LSG
LSG is the standard French abbreviation for the Louis Segond Bible, a widely used Protestant translation of the Scriptures into French.
-
D.
LGSK
LGSK is the ICAO airport code for Skiathos Island National Airport in Greece, known for its short runway and dramatic low-altitude aircraft approaches.
-
E.
RSL
RSL is the shading language used in Pixar's RenderMan system to define the appearance of surfaces, lights, and volumes in high-end computer graphics rendering.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024892fd88190a91133fc88365410 |
completed | March 22, 2026, 5:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07de7df8c8190824d24f729eaa04d |
completed | March 22, 2026, 11:40 p.m. |
Created at: March 22, 2026, 3:45 p.m.