Triple
T5680391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modern English |
E125183
|
entity |
| Predicate | hasLexiconSize |
P18536
|
FINISHED |
| Object | very large vocabulary |
—
|
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: very large vocabulary | Statement: [Modern English, hasLexiconSize, very large vocabulary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexiconSize Context triple: [Modern English, hasLexiconSize, very large vocabulary]
-
A.
hasWordSize
Indicates that an entity possesses or is characterized by a specific word length or word-based size.
-
B.
hasKnownVocabulary
chosen
Indicates that an entity possesses a defined, identifiable set of terms or words that it can recognize or use.
-
C.
lexiconStatus
Indicates the current state or condition of a lexical item within a lexicon, such as whether it is active, deprecated, provisional, or otherwise classified.
-
D.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
E.
hasLimitedCorpus
Indicates that the associated entity possesses only a small or restricted set of available data, texts, or examples for use or analysis.
- 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_69c0082a884c8190a79001bae658941f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0248751bc8190b12aaa42d1ef17e3 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021be59088190a81c880957f666ab |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:44 p.m.