Triple
T36672889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italia in Miniatura |
E905465
|
entity |
| Predicate | numberOfMiniatures |
P55732
|
FINISHED |
| Object | over 270 |
—
|
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 270 | Statement: [Italia in Miniatura, numberOfMiniatures, over 270]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMiniatures Context triple: [Italia in Miniatura, numberOfMiniatures, over 270]
-
A.
hasApproximateNumberOfMiniatures
chosen
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
B.
hasMiniature
Indicates that one entity possesses or includes a smaller-scale representation or model of another entity.
-
C.
numberOfBronzeFigures
Indicates the quantity of bronze figures associated with a given subject or context.
-
D.
numberOfPieces
Indicates the quantity of discrete parts or units into which something is divided or composed.
-
E.
minigamesCount
Indicates the number of minigames associated with or contained within a given entity or context.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0e039481908a4a2666f76c5363 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:12 p.m.