Triple
T2143495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine of Siena |
E47011
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Siena |
E168770
|
NE 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: Siena | Statement: [Catherine of Siena, birthPlace, Siena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siena Context triple: [Catherine of Siena, birthPlace, Siena]
-
A.
Siena
chosen
Siena is a historic Tuscan city renowned for its medieval brick architecture, fan-shaped Piazza del Campo, and the Palio horse race.
-
B.
Arezzo
Arezzo is an ancient Tuscan city in central Italy, historically significant as one of the principal centers of the Etruscan civilization and later a prominent medieval and Renaissance town.
-
C.
Prato
Prato is a historic Tuscan city in central Italy known for its textile industry, medieval architecture, and cultural heritage.
-
D.
Pisa
Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
-
E.
Viterbo
Viterbo is a historic city in central Italy known for its well-preserved medieval center, ancient thermal baths, and role as a papal residence in the 13th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe206db0819095772af5358dca55 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7ef2dda08190b55919f0df935a6d |
completed | March 9, 2026, 8:04 a.m. |
Created at: March 4, 2026, 7:44 p.m.