Triple
T2998663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zayin |
E81131
|
entity |
| Predicate | usedInNumeralSystem |
P6517
|
FINISHED |
| Object | Hebrew numerals |
—
|
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 numerals | Statement: [Zayin, usedInNumeralSystem, Hebrew numerals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInNumeralSystem Context triple: [Zayin, usedInNumeralSystem, Hebrew numerals]
-
A.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
B.
usesRomanNumerals
Indicates that something represents numbers or sequences using the Roman numeral system rather than standard Arabic digits.
-
C.
hasArabicNumeral
Indicates that an entity is associated with, represented by, or expressed using an Arabic numeral.
-
D.
notationSystem
chosen
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
-
E.
hasRomanEquivalent
Indicates that one entity corresponds to or is equivalent to another entity within the context of Roman culture, naming, or classification.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f766408190a5591efce8346bb9 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.