Triple
T25382344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pietroasele Treasure |
E631423
|
entity |
| Predicate | originalNumberOfObjects |
P48434
|
FINISHED |
| Object | over 20 |
—
|
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: over 20 | Statement: [Pietroasele Treasure, originalNumberOfObjects, over 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalNumberOfObjects Context triple: [Pietroasele Treasure, originalNumberOfObjects, over 20]
-
A.
hasNumberOfObjects
chosen
Indicates that an entity is associated with a specific count or quantity of objects.
-
B.
originalNumberOfClasses
Indicates the initial total count of classes before any changes such as additions, removals, or merges occur.
-
C.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
D.
originalNumberOfLeaves
Indicates the initial count of leaves associated with an entity before any changes, losses, or additions occur.
-
E.
originalNumberOfTypes
Indicates the initial total count of distinct types that existed before any changes, filtering, or transformations were applied.
- 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_69e75a8c50788190aabaa9f96710fc43 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 21, 2026, 1:46 p.m.