Triple
T15967259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emir of Qatar Cup |
E387222
|
entity |
| Predicate | trophySignificance |
P120644
|
FINISHED |
| Object | one of the most prestigious sporting trophies in Qatar |
—
|
LITERAL 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: one of the most prestigious sporting trophies in Qatar | Statement: [Emir of Qatar Cup, trophySignificance, one of the most prestigious sporting trophies in Qatar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trophySignificance Context triple: [Emir of Qatar Cup, trophySignificance, one of the most prestigious sporting trophies in Qatar]
-
A.
trophyNameRefersTo
Indicates that a given trophy name refers to, denotes, or is associated with a particular trophy entity.
-
B.
trophy
Indicates that one entity is a trophy awarded or possessed in relation to another entity, typically as a result of winning or achieving something.
-
C.
trophyCount
Indicates the number of trophies associated with a given entity.
-
D.
trophyFeatures
Indicates that a trophy possesses or is characterized by certain features or attributes.
-
E.
trophyOfficialName
Indicates the official, formally recognized name assigned to a particular trophy.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69e173af801c8190bfc0f602831bb594 |
completed | April 16, 2026, 11:41 p.m. |
Created at: April 10, 2026, 4:54 a.m.