Triple
T4938974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María de la Concepción Palacios y Blanco |
E110881
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blanco |
E173667
|
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: Blanco | Statement: [María de la Concepción Palacios y Blanco, familyName, Blanco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanco Context triple: [María de la Concepción Palacios y Blanco, familyName, Blanco]
-
A.
Blanco
chosen
Blanco is a Spanish-language surname most notably associated with Mexican football legend and politician Cuauhtémoc Blanco.
-
B.
Blanc
Blanc is the surname of Mel Blanc, the legendary American voice actor best known for bringing to life many iconic Looney Tunes characters.
-
C.
البيضاء
البيضاء هي مدينة ليبية تقع في الجبل الأخضر بشرق البلاد وتعد من المراكز الإدارية والاقتصادية المهمة هناك.
-
D.
Balderas
Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
-
E.
Pulido
Pulido is a Spanish-language surname borne by various notable individuals in the arts, sports, and public life.
- 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_69bd4415eee08190bdce70276e56a5b4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7088f6e48190bf09e58ab053a4d1 |
completed | March 20, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77bcb8d881908d393223bdea145a |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:31 p.m.