Triple
T27571700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cy-Hawk Trophy |
E696052
|
entity |
| Predicate | locationOfRivalry |
P198784
|
FINISHED |
| Object | State of Iowa |
—
|
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: State of Iowa | Statement: [Cy-Hawk Trophy, locationOfRivalry, State of Iowa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfRivalry Context triple: [Cy-Hawk Trophy, locationOfRivalry, State of Iowa]
-
A.
countryOfRivalry
Indicates that one entity is a country with which another entity has a relationship of rivalry or adversarial competition.
-
B.
nicknameOfRivalryBetween
Indicates that one entity is a nickname or informal title used to refer to a particular rivalry between other entities.
-
C.
rivalryInvolvesCity
Indicates that a rivalry relationship includes or is associated with a particular city as one of its involved locations.
-
D.
hasLocalRivalryVenueWith
Indicates that two entities share a venue or location where a local rivalry between them is regularly contested or expressed.
-
E.
associatedRivalry
Indicates a relationship where one entity is linked to another as its rival, competitor, or opposing counterpart.
- F. None of above. chosen
Provenance (4 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69ff069ddf948190bdfe438953249dd0 |
completed | May 9, 2026, 10:04 a.m. |
Created at: April 27, 2026, 1:43 p.m.