Triple
T12403521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Yeboah |
E296320
|
entity |
| Predicate | hasHighlightGoal |
P104959
|
FINISHED |
| Object | volley vs Liverpool for Leeds United |
—
|
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: volley vs Liverpool for Leeds United | Statement: [Tony Yeboah, hasHighlightGoal, volley vs Liverpool for Leeds United]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighlightGoal Context triple: [Tony Yeboah, hasHighlightGoal, volley vs Liverpool for Leeds United]
-
A.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
B.
hasGoalYear
Indicates that an entity is associated with a specific target year by which a goal or objective is intended to be achieved.
-
C.
hasPlanningGoal
Indicates that an entity is associated with, or directed toward achieving, a specific planning objective or target state.
-
D.
goalType
Indicates the specific category or nature of a goal associated with an entity or action.
-
E.
hasMaintenanceGoal
Indicates that an entity is associated with a specific objective or target related to its upkeep, repair, or ongoing maintenance activities.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e15f21c8190831c9562ffdd4fda |
completed | April 10, 2026, 7:23 p.m. |
Created at: April 8, 2026, 9:55 p.m.