Triple
T15887475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scala |
E385226
|
entity |
| Predicate | isCloseTo |
P45695
|
FINISHED |
| Object | Atrani |
E385224
|
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: Atrani | Statement: [Scala, isCloseTo, Atrani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atrani Context triple: [Scala, isCloseTo, Atrani]
-
A.
Atrani
chosen
Atrani is a tiny, picturesque fishing village and seaside town in southern Italy, known for its medieval architecture and dramatic setting on the Amalfi Coast.
-
B.
Amalner
Amalner is a town in the Indian state of Maharashtra known for its textile industry and as the birthplace of the Wipro company.
-
C.
Udhna
Udhna is an industrial and residential suburb located within the city of Surat in the Indian state of Gujarat.
-
D.
Chalus
Chalus is a coastal city in northern Iran on the Caspian Sea, known for its scenic landscapes and as a popular tourist destination.
-
E.
Kharadi
Kharadi is a rapidly developing suburb in Pune, India, known as a major IT and business hub with modern infrastructure and residential complexes.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1561b6fb48190adcf8277e1895fda |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa95791a48190abc79a6906672098 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:51 a.m.