Triple
T33030648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jack and Jill |
E845153
|
entity |
| Predicate | intendedReadingEnvironment |
P131654
|
FINISHED |
| Object | family setting |
—
|
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: family setting | Statement: [Jack and Jill, intendedReadingEnvironment, family setting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedReadingEnvironment Context triple: [Jack and Jill, intendedReadingEnvironment, family setting]
-
A.
hasReadingEnvironment
chosen
Indicates that an entity is associated with or situated in a particular environment or context in which reading takes place.
-
B.
readingSystem
Indicates a system or device that presents, interprets, or processes written or digital content for a user.
-
C.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
-
D.
readingTechnology
Indicates a relationship where a reading activity involves or is carried out using a particular technology.
-
E.
readingType
Indicates the specific kind or category of reading associated with a measurement, observation, or recorded value.
- 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 1, 2026, 1:24 a.m.