Triple
T28426561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandnes Ulf |
E720094
|
entity |
| Predicate | hasLocalRivalriesIn |
P18267
|
FINISHED |
| Object | Rogaland |
—
|
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: Rogaland | Statement: [Sandnes Ulf, hasLocalRivalriesIn, Rogaland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalRivalriesIn Context triple: [Sandnes Ulf, hasLocalRivalriesIn, Rogaland]
-
A.
hasLocalRivalry
chosen
Indicates that there is an ongoing competitive or adversarial relationship between entities that are geographically close or share the same local area.
-
B.
hasLocalRivalryVenueWith
Indicates that two entities share a venue or location where a local rivalry between them is regularly contested or expressed.
-
C.
associatedRivalry
Indicates a relationship where one entity is linked to another as its rival, competitor, or opposing counterpart.
-
D.
hasNationalRivalryContext
Indicates that there exists a relationship of competitive or adversarial national rivalry between the associated entities, providing the contextual backdrop for their interaction or comparison.
-
E.
hasFanBaseRivalry
Indicates a competitive or antagonistic relationship between the fan bases of two entities.
- F. None of above.
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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 28, 2026, 1:37 a.m.