Triple
T28479294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domenico Scarlatti |
E720645
|
entity |
| Predicate | hasNamesakeStreet |
P52831
|
FINISHED |
| Object | Calle Domenico Scarlatti, Madrid |
—
|
NE NERFINISHED |
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: Calle Domenico Scarlatti, Madrid | Statement: [Domenico Scarlatti, hasNamesakeStreet, Calle Domenico Scarlatti, Madrid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeStreet Context triple: [Domenico Scarlatti, hasNamesakeStreet, Calle Domenico Scarlatti, Madrid]
-
A.
hasStreetNamedAfter
chosen
Indicates that one entity has a street that is named in honor of or after another entity.
-
B.
hasFamousNamesake
Indicates that an entity shares its name with another well-known or notable entity.
-
C.
hasStreetNickname
Indicates that an entity is known by a particular informal or colloquial name used on the street or in everyday speech.
-
D.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
-
E.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
- 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: April 28, 2026, 2:54 a.m.