Triple
T6465833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIFA futsal laws of the game |
E142229
|
entity |
| Predicate | hasOfficialTranslationsIn |
P45244
|
FINISHED |
| Object | multiple languages |
—
|
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: multiple languages | Statement: [FIFA futsal laws of the game, hasOfficialTranslationsIn, multiple languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialTranslationsIn Context triple: [FIFA futsal laws of the game, hasOfficialTranslationsIn, multiple languages]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
C.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
D.
hasOfficial
Indicates that an entity is formally associated with, represented by, or served by a designated official or office-holder.
-
E.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a1159ec81909bbfa9a9d6fa1616 |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:49 p.m.