Triple
T9472249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eliza |
E228419
|
entity |
| Predicate | etymologicalRoot |
P453
|
FINISHED |
| Object | Elisheva |
E489909
|
NE 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: Elisheva | Statement: [Eliza, etymologicalRoot, Elisheva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elisheva Context triple: [Eliza, etymologicalRoot, Elisheva]
-
A.
Elisheva
chosen
Elisheva is a Hebrew female given name, traditionally interpreted as meaning "my God is an oath" or "God is my satisfaction."
-
B.
Miryam
Miryam is the Hebrew form of the name of the Virgin Mary, the mother of Jesus in Christian tradition.
-
C.
Peninnah
Peninnah is a biblical figure, one of Elkanah’s wives, known for provoking and taunting Hannah over her childlessness in the First Book of Samuel.
-
D.
Miriam
Miriam is a central fictional character in Nathaniel Hawthorne’s novel "The Marble Faun," portrayed as a mysterious and artistically gifted woman with a troubled past.
-
E.
Miriam
Miriam is a prominent biblical figure known as the sister of Moses and Aaron and as a prophetess during the Exodus of the Israelites from Egypt.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca847162c48190b079076c9595513c |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fef6f288190b2d158c829b31de9 |
completed | April 1, 2026, 8:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122cd0728819088f6c832cd90d832 |
completed | April 4, 2026, 2:40 p.m. |
Created at: March 30, 2026, 7:54 p.m.