Triple
T4868081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let Us Compare Mythologies |
E109019
|
entity |
| Predicate | hasPoemCountApprox |
P32364
|
FINISHED |
| Object | around 40 poems |
—
|
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: around 40 poems | Statement: [Let Us Compare Mythologies, hasPoemCountApprox, around 40 poems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoemCountApprox Context triple: [Let Us Compare Mythologies, hasPoemCountApprox, around 40 poems]
-
A.
approximateNumberOfPoems
chosen
Indicates an estimated or roughly calculated count of poems associated with an entity.
-
B.
containsNumberOfPoems
Indicates that one entity includes or specifies a particular quantity of poems associated with it.
-
C.
containsPoemsBy
Indicates that one entity (such as a collection or publication) includes poems authored by another entity.
-
D.
containsPoem
Indicates that one entity includes or holds a poem as part of its contents.
-
E.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d7bb0b88190bbc24498619910fc |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.