Triple
T30114368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1998 FIFA World Cup qualification |
E765371
|
entity |
| Predicate | OFCAllocatedSlots |
P168461
|
FINISHED |
| Object | 0.5 |
—
|
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: 0.5 | Statement: [1998 FIFA World Cup qualification, OFCAllocatedSlots, 0.5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: OFCAllocatedSlots Context triple: [1998 FIFA World Cup qualification, OFCAllocatedSlots, 0.5]
-
A.
numberOfTimeSlotsPerCarrier
Indicates the quantity of discrete time slots that are allocated or assigned to each individual carrier.
-
B.
numberOfTimeSlotsPerFrame
Indicates the total count of discrete time slots that are contained within a single frame in a time-structured system or protocol.
-
C.
maximumSlotsRecommended
Indicates the highest number of slots that is advised or suggested to be used in a given context.
-
D.
hasNumberOfPrincipalOdu
Indicates the quantity of principal Odu associated with an entity.
-
E.
maxSlotsPerSystem
Indicates the maximum number of slots that are allowed or can be allocated within a single system.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67dc294488190af7314b78253404e |
completed | May 2, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69f673c664f08190b4d66cdc305e10db |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f6749f205c81909d1aacf462912eee |
completed | May 2, 2026, 10:03 p.m. |
Created at: April 29, 2026, 7:11 p.m.