Triple
T2569886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgian Super Cup |
E57638
|
entity |
| Predicate | firstLeg |
P40286
|
FINISHED |
| Object | not applicable (single match format) |
—
|
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: not applicable (single match format) | Statement: [Georgian Super Cup, firstLeg, not applicable (single match format)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstLeg Context triple: [Georgian Super Cup, firstLeg, not applicable (single match format)]
-
A.
firstWord
Indicates that one entity is the first word in the sequence or text associated with another entity.
-
B.
firstStageType
Indicates that one entity is the type or category of the first stage or initial phase associated with another entity.
-
C.
firstLocation
Indicates the initial or primary place where an entity is situated, originates, or where an event or relationship begins.
-
D.
firstStageName
Indicates that one entity is the initial or earliest stage name associated with another entity in a sequence or lifecycle.
-
E.
firstTier
Indicates that one entity occupies the highest or primary level, rank, or priority relative to others in a hierarchical structure.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd380d6e081909c124e8a0b7feef3 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0cc8d308190ae7aa32b8f5ae2e5 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1aa13a08190a8757c017d8a2478 |
completed | March 7, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:48 p.m.