Triple
T15741580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latin I |
E381613
|
entity |
| Predicate | languageSkillEmphasis |
P45342
|
FINISHED |
| Object | reading |
—
|
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: reading | Statement: [Latin I, languageSkillEmphasis, reading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageSkillEmphasis Context triple: [Latin I, languageSkillEmphasis, reading]
-
A.
skillEmphasis
chosen
Indicates that a particular skill is given special focus, priority, or importance within a context such as a role, task, or curriculum.
-
B.
skilledIn
Indicates that an entity possesses ability, expertise, or proficiency in performing or using another entity (such as a task, tool, or domain).
-
C.
focusesOnLanguage
Indicates that an entity’s primary attention, activity, or content is directed toward language as its main subject or concern.
-
D.
languageCapacity
Indicates the extent to which an entity is able to understand, produce, or otherwise use language.
-
E.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0052c6208819098165d61d378d13b |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:46 a.m.