Triple
T945694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emilio Mola |
E20408
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Mola
Mola is a Spanish surname most notably associated with Emilio Mola, a key Nationalist general during the Spanish Civil War.
|
E113074
|
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: Mola | Statement: [Emilio Mola, familyName, Mola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mola Context triple: [Emilio Mola, familyName, Mola]
-
A.
Navalcarnero
Navalcarnero is a historic town and municipality in central Spain known for its traditional architecture, wine production, and location southwest of Madrid.
-
B.
Dorado
Dorado is a coastal municipality in northern Puerto Rico known for its upscale resorts, golf courses, and residential communities.
-
C.
Dorado
Dorado is a southern sky constellation known for containing most of the Large Magellanic Cloud and the southern portion of the Milky Way’s satellite galaxy.
-
D.
Fisk
Fisk is a surname most famously associated with Carlton Fisk, a Hall of Fame Major League Baseball catcher known for his long career with the Boston Red Sox and Chicago White Sox.
-
E.
Bruinisse
Bruinisse is a fishing village and tourist destination in the Dutch province of Zeeland, known for its mussel industry and location on the Grevelingen.
- 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: Mola Triple: [Emilio Mola, familyName, Mola]
Generated description
Mola is a Spanish surname most notably associated with Emilio Mola, a key Nationalist general during the Spanish Civil War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mola Target entity description: Mola is a Spanish surname most notably associated with Emilio Mola, a key Nationalist general during the Spanish Civil War.
-
A.
Navalcarnero
Navalcarnero is a historic town and municipality in central Spain known for its traditional architecture, wine production, and location southwest of Madrid.
-
B.
Dorado
Dorado is a coastal municipality in northern Puerto Rico known for its upscale resorts, golf courses, and residential communities.
-
C.
Dorado
Dorado is a southern sky constellation known for containing most of the Large Magellanic Cloud and the southern portion of the Milky Way’s satellite galaxy.
-
D.
Fisk
Fisk is a surname most famously associated with Carlton Fisk, a Hall of Fame Major League Baseball catcher known for his long career with the Boston Red Sox and Chicago White Sox.
-
E.
Bruinisse
Bruinisse is a fishing village and tourist destination in the Dutch province of Zeeland, known for its mussel industry and location on the Grevelingen.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3a61b648190b1b6c932e047e161 |
completed | March 1, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac119a80e08190b0179f8d413e06fd |
completed | March 7, 2026, 11:52 a.m. |
| NEDg | Description generation | batch_69ac12bac21881908b2a6acf2c241c23 |
completed | March 7, 2026, 11:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac132f09448190b5f789f90328f81f |
completed | March 7, 2026, 11:59 a.m. |
Created at: March 1, 2026, 7:40 p.m.