Triple
T17280230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Maria |
E419505
|
entity |
| Predicate | etymologicalOriginOfComponent_Anna |
P108324
|
FINISHED |
| Object | Hebrew name Hannah |
—
|
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: Hebrew name Hannah | Statement: [Anna Maria, etymologicalOriginOfComponent_Anna, Hebrew name Hannah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologicalOriginOfComponent_Anna Context triple: [Anna Maria, etymologicalOriginOfComponent_Anna, Hebrew name Hannah]
-
A.
etymologicalRootName
chosen
Indicates that one name is derived from, or originates etymologically in, another name.
-
B.
etymologyProposedBy
Indicates that a proposed origin or derivation of a word or term is attributed to a particular person or source.
-
C.
etymologicalNote
Indicates that there is a note explaining the origin, historical development, or source language of a term or name.
-
D.
possibleNameEtymology
Indicates a hypothesized or suggested origin or derivation of an entity’s name from another term, source, or linguistic root.
-
E.
etymologyReason
Indicates the reason, source, or origin explaining how or why a term acquired its particular etymology.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e43329904c8190a4cbc856b9b94ff8 |
completed | April 19, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69e3832c3b98819091967ac7e91ba316 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:40 a.m.