Triple
T3343469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 FIFA World Cup |
E70312
|
entity |
| Predicate | firstWorldCupHeldInMonths |
P47335
|
FINISHED |
| Object | November–December |
—
|
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: November–December | Statement: [2022 FIFA World Cup, firstWorldCupHeldInMonths, November–December]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstWorldCupHeldInMonths Context triple: [2022 FIFA World Cup, firstWorldCupHeldInMonths, November–December]
-
A.
isFirstWorldCupHeldIn
Indicates that a country's first participation in the FIFA World Cup took place in the specified host nation or location.
-
B.
wasFirstWorldCupWith
Indicates that the referenced World Cup tournament was the first one to feature or include the specified characteristic, rule, format, or element.
-
C.
worldCupHostYear
Indicates the year in which a particular country or location served as the host of the FIFA World Cup tournament.
-
D.
worldCupAppearanceYear
Indicates the specific year in which an entity participated in a FIFA World Cup tournament.
-
E.
worldCupTitleYear
Indicates the specific year in which an entity won or held a FIFA World Cup title.
- 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_69ad85a405e48190b6e68de7cf9f319e |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb1f06f8c8190a6b7c56ac3f5ff07 |
completed | March 8, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada52716ec81908e89688a81039394 |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:12 p.m.