Triple
T32092570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France vs Argentina 2007 Rugby World Cup opening match |
E819634
|
entity |
| Predicate | FranceScore |
P174127
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [France vs Argentina 2007 Rugby World Cup opening match, FranceScore, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FranceScore Context triple: [France vs Argentina 2007 Rugby World Cup opening match, FranceScore, 12]
-
A.
ratingFrance
Indicates that an entity assigns or holds a rating or evaluation specifically related to France.
-
B.
strengthFrance
Indicates a relationship where a level, measure, or attribute of strength is associated specifically with France.
-
C.
economicRankInFrance
Indicates the relative economic standing or ranking of an entity within the context of France’s economy.
-
D.
FrenchObjective
Indicates that an entity serves as the goal, target, or object of an action or relation specifically within a French linguistic or contextual framework.
-
E.
populationRankInFrance
Indicates the relative position of an entity in an ordered list based on its population size within France.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bcc425588190afd0dceba43ed79f |
completed | May 3, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
| PDg | Predicate description generation | batch_69f6bbbe23d48190b2aa662d69b41900 |
completed | May 3, 2026, 3:06 a.m. |
Created at: May 1, 2026, 12:25 a.m.