Triple
T35507160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orsolya |
E1026180
|
entity |
| Predicate | hasDiminutiveMeaning |
P456
|
FINISHED |
| Object | little bear |
—
|
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: little bear | Statement: [Orsolya, hasDiminutiveMeaning, little bear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiminutiveMeaning Context triple: [Orsolya, hasDiminutiveMeaning, little bear]
-
A.
hasDiminutive
chosen
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
B.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
C.
hasMeaningByDerivation
Indicates that the meaning of one entity is obtained or derived from another entity, rather than being original or independent.
-
D.
hasMeaningOfEpithet
Indicates that one entity expresses or conveys the meaning or sense of another entity’s epithet.
-
E.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
- 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_69f76dfd61208190b93ec6dc439cab41 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff48199b1c8190bb05872f8a4f4673 |
completed | May 9, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69ff4746b1cc8190854f70a124df7d04 |
completed | May 9, 2026, 2:40 p.m. |
Created at: May 3, 2026, 4:04 p.m.