Triple
T3637379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernando Botero |
E77104
|
entity |
| Predicate | livedIn |
P75
|
FINISHED |
| Object |
Pietrasanta
Pietrasanta is a historic Tuscan town in Italy renowned for its marble workshops, sculpture studios, and vibrant community of international artists.
|
E429047
|
NE FINISHED |
How this triple was built (4 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: Pietrasanta | Statement: [Fernando Botero, livedIn, Pietrasanta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pietrasanta Context triple: [Fernando Botero, livedIn, Pietrasanta]
-
A.
Pietrasanta
Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
-
B.
Denia
Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
-
C.
Pontevedra
Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
-
D.
Pontevedra
Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
-
E.
Quarteira
Quarteira is a coastal town in Portugal’s Algarve region known for its long sandy beaches, seaside promenade, and role as a popular holiday resort.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pietrasanta Triple: [Fernando Botero, livedIn, Pietrasanta]
Generated description
Pietrasanta is a historic Tuscan town in Italy renowned for its marble workshops, sculpture studios, and vibrant community of international artists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pietrasanta Target entity description: Pietrasanta is a historic Tuscan town in Italy renowned for its marble workshops, sculpture studios, and vibrant community of international artists.
-
A.
Pietrasanta
Pietrasanta is an Italian surname of likely toponymic origin, associated with individuals such as Angela Maria Pietrasanta.
-
B.
Denia
Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
-
C.
Pontevedra
Pontevedra is a coastal municipality in the province of Capiz in the Philippines, known for its fishing communities and agricultural economy.
-
D.
Pontevedra
Pontevedra is a coastal province in northwestern Spain known for its historic towns, Atlantic landscapes, and location within the autonomous community of Galicia.
-
E.
Quarteira
Quarteira is a coastal town in Portugal’s Algarve region known for its long sandy beaches, seaside promenade, and role as a popular holiday resort.
- F. None of above. chosen
Provenance (5 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_69ad85dd0be48190b738990cb20c4731 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc328e5e481909d26318c743bc84a |
completed | March 8, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5c6e3fbbc81908594bb7c9b02f873 |
completed | March 14, 2026, 8:36 p.m. |
| NEDg | Description generation | batch_69b5c779d28c81909fdb37adb045684c |
completed | March 14, 2026, 8:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5c7f6195481909167c972e1838cc9 |
completed | March 14, 2026, 8:41 p.m. |
Created at: March 8, 2026, 3:24 p.m.