Triple
T4354737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ave Maria Grotto |
E98118
|
entity |
| Predicate | hasApproximateNumberOfMiniatures |
P55732
|
FINISHED |
| Object | over 100 |
—
|
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 100 | Statement: [Ave Maria Grotto, hasApproximateNumberOfMiniatures, over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfMiniatures Context triple: [Ave Maria Grotto, hasApproximateNumberOfMiniatures, over 100]
-
A.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
B.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
C.
hasNumberOfSmallerIslets
Indicates that an entity is associated with a specified count of smaller islets related to it.
-
D.
hasApproximateNumberOfTombs
Indicates that an entity is associated with a tomb count that is approximate rather than exact.
-
E.
numberOfCapsules
Indicates the quantity or count of capsules associated with an entity or event.
- F. None of above. chosen
Provenance (4 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_69b3454965f881908c41190bb22f0e4b |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351c3aa1c8190aacebb8e80e5f2f8 |
completed | March 12, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69b34f51ed7c8190b7bf5f44b56b730d |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:16 p.m.