Triple
T8604465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toledo, Spain |
E203762
|
entity |
| Predicate | demonym |
P191
|
FINISHED |
| Object |
Toledano
Toledano is the Spanish term used to refer to people or things originating from the historic city of Toledo in central Spain.
|
E744960
|
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: Toledano | Statement: [Toledo, Spain, demonym, Toledano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toledano Context triple: [Toledo, Spain, demonym, Toledano]
-
A.
Cordovero
Cordovero is a Sephardic Jewish surname most famously associated with the 16th-century Kabbalist Rabbi Moshe Cordovero of Safed.
-
B.
Yehudi
Yehudi is a masculine given name most famously associated with the renowned violinist Yehudi Menuhin.
-
C.
Goldshteyn
Goldshteyn is a variant spelling of the Jewish surname Goldstein, commonly found in Russian and Yiddish transliterations.
-
D.
Calvero
Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
-
E.
Crescentino
Crescentino is a municipality in the Piedmont region of northwestern Italy, situated in the province of Vercelli.
- 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: Toledano Triple: [Toledo, Spain, demonym, Toledano]
Generated description
Toledano is the Spanish term used to refer to people or things originating from the historic city of Toledo in central Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Toledano Target entity description: Toledano is the Spanish term used to refer to people or things originating from the historic city of Toledo in central Spain.
-
A.
Cordovero
Cordovero is a Sephardic Jewish surname most famously associated with the 16th-century Kabbalist Rabbi Moshe Cordovero of Safed.
-
B.
Yehudi
Yehudi is a masculine given name most famously associated with the renowned violinist Yehudi Menuhin.
-
C.
Goldshteyn
Goldshteyn is a variant spelling of the Jewish surname Goldstein, commonly found in Russian and Yiddish transliterations.
-
D.
Calvero
Calvero is the aging, once-famous clown portrayed by Charlie Chaplin in the 1952 film "Limelight," struggling with obscurity and seeking redemption through helping a young dancer.
-
E.
Crescentino
Crescentino is a municipality in the Piedmont region of northwestern Italy, situated in the province of Vercelli.
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46dd8ff8819081ef269192047488 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea8f8dfa4819080c8ed475a84be41 |
completed | April 2, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69cea9d0dad0819095134f6f8cafb4c0 |
completed | April 2, 2026, 5:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceaa7025388190a3f17aca46d4858e |
completed | April 2, 2026, 5:42 p.m. |
Created at: March 30, 2026, 6:24 p.m.