Triple
T18034176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Louise |
E431463
|
entity |
| Predicate | hasEtymologicalComponentOrigin |
P124938
|
FINISHED |
| Object | Mary from Hebrew Miryam |
—
|
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: Mary from Hebrew Miryam | Statement: [Mary Louise, hasEtymologicalComponentOrigin, Mary from Hebrew Miryam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEtymologicalComponentOrigin Context triple: [Mary Louise, hasEtymologicalComponentOrigin, Mary from Hebrew Miryam]
-
A.
hasEtymologicalBasis
chosen
Indicates that one term, name, or expression is derived from, based on, or historically formed from the other in terms of linguistic origin.
-
B.
hasEtymologyConcept
Indicates that something derives its origin, form, or meaning from a particular etymological concept or source.
-
C.
etymologyStatus
Indicates the status or reliability classification of an etymological explanation for a term or name.
-
D.
hasEtymologyDetail
Indicates a relationship where additional explanatory or contextual information about the origin or derivation of a term is provided.
-
E.
hasLatinEtymology
Indicates that something originates from or is derived from a Latin word or linguistic root.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be38766c8190ae95701f4575469c |
completed | April 19, 2026, 11:36 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.