Triple
T4182995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francisca |
E88236
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Franca |
E293506
|
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: Franca | Statement: [Francisca, hasDiminutive, Franca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Franca Context triple: [Francisca, hasDiminutive, Franca]
-
A.
Franca
chosen
Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
-
B.
Fransat
Fransat is a French free-to-air satellite television platform that provides access to the national digital terrestrial TV channels across France.
-
C.
Włochy
Włochy is a district in the southwestern part of Warsaw, Poland, known for its mix of residential areas, industrial zones, and major transport infrastructure including the city’s main airport.
-
D.
Sansobbia
Sansobbia is a small river in the Liguria region of northwestern Italy that flows through the municipality of Albisola Superiore before reaching the Ligurian Sea.
-
E.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0307a0b481909c7287402a8c78c4 |
completed | March 9, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589fbcc5881908f245bb377082dcc |
completed | March 14, 2026, 4:16 p.m. |
Created at: March 9, 2026, 3:45 p.m.