Triple
T10361522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hareton Earnshaw |
E244143
|
entity |
| Predicate | learnsToRead |
P93869
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hareton Earnshaw, learnsToRead, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnsToRead Context triple: [Hareton Earnshaw, learnsToRead, true]
-
A.
readingAid
Indicates that one entity assists or facilitates another entity’s ability to read or engage in reading activities.
-
B.
learnedToReadAndWriteIn
Indicates that an entity acquired the skills of reading and writing during a period associated with a specified context, such as a place, institution, or time.
-
C.
learnsLanguageFrom
Indicates that one entity acquires or improves knowledge of a language through instruction, exposure, or guidance provided by another entity.
-
D.
reading
Indicates that an entity is engaged in the activity of interpreting and understanding written or printed material from another entity or source.
-
E.
containsReading
Indicates that one entity includes or encompasses a particular reading (such as a measurement, value, or interpretation) within it.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e96209548190957368ee8c6a9ec3 |
completed | April 7, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
| PDg | Predicate description generation | batch_69d4e91ce2008190af252c140370b7f2 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 11:59 a.m.