Triple
T37915058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comparative Literature and Culture |
E945791
|
entity |
| Predicate | comparesAcross |
P51217
|
FINISHED |
| Object | languages |
—
|
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: languages | Statement: [Comparative Literature and Culture, comparesAcross, languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comparesAcross Context triple: [Comparative Literature and Culture, comparesAcross, languages]
-
A.
comparisonUnit
Indicates that one entity serves as the reference or baseline unit against which another entity is compared or measured.
-
B.
comparisonAspect
chosen
Indicates that two or more entities are being compared specifically with respect to a particular shared attribute or dimension.
-
C.
comparisonReason
Indicates that one entity is being compared to another specifically due to a stated reason, motive, or basis for the comparison.
-
D.
comparisonType
Indicates the specific kind of comparison being made between two or more values or entities (e.g., equality, inequality, ordering, or similarity).
-
E.
comparativeScale
Indicates a relationship where one entity is evaluated relative to another along a shared scale or dimension (such as size, intensity, or degree).
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.