Triple
T25771629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palio di Siena |
E649035
|
entity |
| Predicate | numberOfContrade |
P190471
|
FINISHED |
| Object | 17 |
—
|
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: 17 | Statement: [Palio di Siena, numberOfContrade, 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfContrade Context triple: [Palio di Siena, numberOfContrade, 17]
-
A.
numberOfConflicts
Indicates the count of distinct conflicts associated with or involving a given entity or situation.
-
B.
hasNumberOfConcourses
Indicates the relationship specifying how many concourses are associated with a given entity.
-
C.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
transactionCounterparty
Indicates that one entity is the other party involved in a financial or commercial transaction with the subject entity.
-
E.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
- 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_69e7ab333b508190b6d708d8d9a328ed |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fcc7779d248190afdb348a95375443 |
completed | May 7, 2026, 5:10 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
| PDg | Predicate description generation | batch_69fcc73264e08190b0b5917f32226fae |
completed | May 7, 2026, 5:09 p.m. |
Created at: April 22, 2026, 5:30 a.m.