Triple
T8432118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nesite |
E199136
|
entity |
| Predicate | modernTermUsedBy |
P63299
|
FINISHED |
| Object | scholars of ancient Anatolia |
—
|
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: scholars of ancient Anatolia | Statement: [Nesite, modernTermUsedBy, scholars of ancient Anatolia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernTermUsedBy Context triple: [Nesite, modernTermUsedBy, scholars of ancient Anatolia]
-
A.
modernUse
Indicates how something is currently used or applied in modern times.
-
B.
usedTerm
Indicates that one entity employed, referenced, or applied a particular term in some context.
-
C.
modernEquivalent
Indicates that one entity serves as the contemporary or updated counterpart of another earlier or traditional entity.
-
D.
termAlsoUsedFor
Indicates that one term is also used to refer to the same or closely related concept as another term.
-
E.
hasModernScholarlyTerm
chosen
Indicates that there exists a contemporary academic or scholarly term that corresponds to or designates the given entity or concept.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:07 p.m.