Triple
T5450878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oration on the Dignity of Man |
E122365
|
entity |
| Predicate | circaWordCount |
P6006
|
FINISHED |
| Object | short treatise-length work |
—
|
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: short treatise-length work | Statement: [Oration on the Dignity of Man, circaWordCount, short treatise-length work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: circaWordCount Context triple: [Oration on the Dignity of Man, circaWordCount, short treatise-length work]
-
A.
wordCount
Indicates the total number of words contained in a given text or linguistic unit.
-
B.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
C.
lengthInWords
chosen
Indicates the number of words that make up the length of something, typically a text or expression.
-
D.
approximateNumberOfVerses
Indicates an estimated or approximate count of verses associated with an entity.
-
E.
wordLength
Indicates that there is a relationship specifying the number of characters (length) in a given word.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.