Triple
T5183829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ælfric’s Colloquy |
E116982
|
entity |
| Predicate | hasGlossesIn |
P60969
|
FINISHED |
| Object | Old 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: Old English | Statement: [Ælfric’s Colloquy, hasGlossesIn, Old English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGlossesIn Context triple: [Ælfric’s Colloquy, hasGlossesIn, Old English]
-
A.
hasMultilingualGlosses
chosen
Indicates that an entity is associated with glosses or explanatory labels available in multiple languages.
-
B.
hasVocabularyFrom
Indicates that one entity’s vocabulary, terminology, or set of terms is derived from, based on, or taken from another entity.
-
C.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
-
D.
hasCognate
Indicates that two linguistic forms in different languages share a common historical origin, typically descending from the same ancestral word.
-
E.
hasConnotation
Indicates that one entity carries an implied or associated meaning, tone, or emotional nuance in relation to another entity.
- 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_69bd44620ff48190bcac01782107a397 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd799eb90c8190b738e9478699180f |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b7e8b4819092ec3965e11f2dea |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:46 p.m.