Triple
T25224286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Klingon language |
E632049
|
entity |
| Predicate | hasLexiconSizeEstimate |
P67671
|
FINISHED |
| Object | thousands of words |
—
|
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: thousands of words | Statement: [Klingon language, hasLexiconSizeEstimate, thousands of words]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexiconSizeEstimate Context triple: [Klingon language, hasLexiconSizeEstimate, thousands of words]
-
A.
hasVocabularySize
Indicates the size or number of vocabulary items possessed or used by an entity.
-
B.
hasLexiconSource
Indicates that a lexical item or entry is derived from, documented in, or otherwise sourced from a particular lexicon or lexical resource.
-
C.
hasApproximateNumberOfGlosses
Indicates that an entity is associated with an estimated or non-exact count of glosses (explanatory notes or definitions).
-
D.
hasLexiconPreservedIn
Indicates that the lexicon of one entity is preserved, recorded, or stored within another entity.
-
E.
hasApproximateNumberOfAttestedWords
chosen
Indicates that an entity is associated with an estimated or approximate count of words that are documented or attested for it.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 21, 2026, 1:03 p.m.