Triple
T7669707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ugaritic language |
E173716
|
entity |
| Predicate | numberOfSignsInAlphabet |
P37173
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Ugaritic language, numberOfSignsInAlphabet, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSignsInAlphabet Context triple: [Ugaritic language, numberOfSignsInAlphabet, 30]
-
A.
numberOfSigns
chosen
Indicates the quantity of signs associated with or present in relation to a given entity or context.
-
B.
alphabetSizeLatin
Indicates the number of distinct letters in the Latin alphabet used in a given context or system.
-
C.
alphabet
Indicates that one entity is an alphabet or set of symbols used for representing elements (such as characters or tokens) in relation to another entity.
-
D.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
E.
alphabetType
Indicates the type or classification of an alphabet used by a writing system or language.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7063dab1881909598b04999b8b690 |
completed | March 27, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69c7015f7430819099d3ea2781b7cee2 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4 p.m.