Triple
T10063029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Historic Centre of San Gimignano |
E213032
|
entity |
| Predicate | maximumNumberOfMedievalTowers |
P5319
|
FINISHED |
| Object | 72 |
—
|
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: 72 | Statement: [Historic Centre of San Gimignano, maximumNumberOfMedievalTowers, 72]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfMedievalTowers Context triple: [Historic Centre of San Gimignano, maximumNumberOfMedievalTowers, 72]
-
A.
numberOfTowers
chosen
Indicates the quantity of towers associated with or contained by a given entity.
-
B.
storeysOfTallestTower
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
C.
eraOfMainCastle
Indicates the historical period or era during which the main castle associated with an entity was built, used, or most prominent.
-
D.
maximumNumberOfKnights
Indicates the greatest possible number of knights that can be present or placed in a given context or configuration.
-
E.
castleBuilt
Indicates that a castle has been constructed or established, typically by a specific agent or during a particular time period.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcfd4e4ac8190a37061b4082caa48 |
completed | April 2, 2026, 2:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 8:58 p.m.