Triple
T348487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanakh |
E6991
|
entity |
| Predicate | abbreviationOrigin |
P8733
|
FINISHED |
| Object | initial letters of Torah Nevi'im Ketuvim |
—
|
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: initial letters of Torah Nevi'im Ketuvim | Statement: [Tanakh, abbreviationOrigin, initial letters of Torah Nevi'im Ketuvim]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: abbreviationOrigin Context triple: [Tanakh, abbreviationOrigin, initial letters of Torah Nevi'im Ketuvim]
-
A.
abbreviation
Indicates that one term is a shortened or contracted form that stands for another, longer expression.
-
B.
hasAcronymOrigin
chosen
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
C.
notAbbreviationOf
Indicates that one term is explicitly asserted not to be an abbreviation or shortened form of another term.
-
D.
hasNameAbbreviation
Indicates that an entity is associated with a shortened or abbreviated form of its full name.
-
E.
etymologyType
Indicates the specific kind or category of etymological relationship that links a term to its linguistic origin or source.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1c1c908190b3a01de893207ed1 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e955d1f88190bd687c46fa7c5469 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.