Triple
T30968789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elegies (Propertius) |
E789032
|
entity |
| Predicate | alternateCounting |
P99808
|
FINISHED |
| Object | sometimes counted as 5 books |
—
|
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: sometimes counted as 5 books | Statement: [Elegies (Propertius), alternateCounting, sometimes counted as 5 books]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternateCounting Context triple: [Elegies (Propertius), alternateCounting, sometimes counted as 5 books]
-
A.
alternativeCounting
chosen
Indicates that there exists another valid way of counting or enumerating the same set of items or events, distinct from the primary counting method.
-
B.
areCountedBy
Indicates that one entity serves as the counting mechanism, record, or process by which the quantity of another entity is determined.
-
C.
count
Indicates the numerical quantity or total number of instances of a specified entity or event.
-
D.
ordinalNumber
Indicates the position or rank of an entity within an ordered sequence (e.g., first, second, third).
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- 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_69f224c3a6b48190951add9b7b7f0271 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 29, 2026, 8:54 p.m.