Triple
T2463451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLII |
E54586
|
entity |
| Predicate | numeralValueOfL |
P7465
|
FINISHED |
| Object | 50 |
—
|
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: 50 | Statement: [XLII, numeralValueOfL, 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numeralValueOfL Context triple: [XLII, numeralValueOfL, 50]
-
A.
valueOfL
Indicates that one entity represents the numerical or quantitative value associated with another entity, typically in a specific context or measurement.
-
B.
RomanNumeral
chosen
Indicates that something is represented or written using the Roman numeral system.
-
C.
usesRomanNumerals
Indicates that something represents numbers or sequences using the Roman numeral system rather than standard Arabic digits.
-
D.
hasNumericValueInGreekNumerals
Indicates that an entity is associated with a specific numeric value expressed using Greek numeral notation.
-
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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd2bc7b5481908b3664495e99f1a4 |
completed | March 7, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69abd0b3ea308190a6d8499c2a542c50 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.