Triple
T24177442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enosis with Greece |
E599319
|
entity |
| Predicate | hasOpposingGoal |
P132694
|
FINISHED |
| Object | Taksim (partition of Cyprus) |
—
|
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: Taksim (partition of Cyprus) | Statement: [Enosis with Greece, hasOpposingGoal, Taksim (partition of Cyprus)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingGoal Context triple: [Enosis with Greece, hasOpposingGoal, Taksim (partition of Cyprus)]
-
A.
hasOppositionGoal
chosen
Indicates that one entity’s goal is in direct conflict with, or aims to prevent the achievement of, another entity’s goal.
-
B.
ownGoalBy
Indicates that a goal was accidentally scored against a team by the specified player (i.e., the player scored an own goal).
-
C.
officialGoal
Indicates that something is the formally designated or institutionally recognized objective or target of an entity.
-
D.
ownGoalBeneficiaryTeam
Indicates the team that gains the scoring benefit when an own goal is committed against it.
-
E.
numberOfGoals
Indicates the total count of goals scored or achieved by an entity in a given context.
- 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_69e288cca05481908faeb1563711114a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:34 p.m.