Triple
T6882067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phillis Wheatley |
E158820
|
entity |
| Predicate | learnedToReadAndWriteIn |
P73925
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Phillis Wheatley, learnedToReadAndWriteIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnedToReadAndWriteIn Context triple: [Phillis Wheatley, learnedToReadAndWriteIn, English]
-
A.
literacyStatus
Indicates whether an entity possesses the ability to read and write, or its level of literacy.
-
B.
canBeWrittenIn
Indicates that something is capable of being expressed, encoded, or represented using a particular language, notation, or medium.
-
C.
currentlyWrittenIn
Indicates that a work or document is, at the present time, expressed or composed in a particular language or writing system.
-
D.
writingSystemUsedIn
Indicates that a particular writing system is employed for written communication within a given language, region, or context.
-
E.
schoolPhase
Indicates the specific stage or level within an educational system at which the related entity operates or applies.
- 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_69c688342f6c8190ad7eea6ba262db99 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8e90c9481908d00634f67fa71f8 |
completed | March 27, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b53e9881909ec298daa9f1913b |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:23 p.m.