Triple
T12878250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niall Quinn |
E308019
|
entity |
| Predicate | hasGivenCommentaryFor |
P72470
|
FINISHED |
| Object | television football coverage |
—
|
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: television football coverage | Statement: [Niall Quinn, hasGivenCommentaryFor, television football coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenCommentaryFor Context triple: [Niall Quinn, hasGivenCommentaryFor, television football coverage]
-
A.
hasCommentaryOn
Indicates that one entity provides commentary, explanation, or evaluative remarks about another entity.
-
B.
hasCommentaryIn
Indicates that an entity is discussed, analyzed, or annotated within a specific commentary work or source.
-
C.
hasCommentaryForm
Indicates that one entity exists in, or is associated with, a commentary version or format of another entity.
-
D.
commentatedFor
chosen
Indicates that one entity provided live or recorded commentary or analysis for an event, performance, or broadcast on behalf of another entity (such as an organization, channel, or client).
-
E.
typeOfCommentary
Indicates that one piece of commentary is a specific kind or subtype of another, more general category of commentary.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:38 p.m.