Triple
T35403100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orlando City SC vs Sacramento Republic FC |
E1023288
|
entity |
| Predicate | cupName |
P40472
|
FINISHED |
| Object | Lamar Hunt U.S. Open Cup |
—
|
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: Lamar Hunt U.S. Open Cup | Statement: [Orlando City SC vs Sacramento Republic FC, cupName, Lamar Hunt U.S. Open Cup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cupName Context triple: [Orlando City SC vs Sacramento Republic FC, cupName, Lamar Hunt U.S. Open Cup]
-
A.
typeOfCup
chosen
Indicates the specific kind or category of cup that an entity is associated with or classified as.
-
B.
cupWonWith
Indicates that a particular cup or tournament victory was achieved using or in association with a specified entity (such as a team, player, or equipment).
-
C.
coffeeDesignation
Indicates that one entity is designated or classified as a particular type, role, or category of coffee in relation to another entity.
-
D.
coffeeBrand
Indicates that one entity is a brand associated with the production or marketing of coffee products for the other entity.
-
E.
coffeeDesignationType
Indicates the specific classification or type designation assigned to a coffee (e.g., by quality, origin, or regulatory category).
- 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_69f76df43ca4819098711ca4370f1bb9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7953da17c8190a0a038341f387831 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.