Triple
T15987864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theresa Lopez-Fitzgerald |
E387743
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Lopez-Fitzgerald
Lopez-Fitzgerald is the surname of a central working-class family featured in the American soap opera "Passions."
|
E1187972
|
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: Lopez-Fitzgerald | Statement: [Theresa Lopez-Fitzgerald, familyName, Lopez-Fitzgerald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lopez-Fitzgerald Context triple: [Theresa Lopez-Fitzgerald, familyName, Lopez-Fitzgerald]
-
A.
López-Salido
López-Salido is a Spanish surname most notably associated with economist J. David López-Salido, known for his work in macroeconomics and monetary policy.
-
B.
López
López is a common Spanish surname widely borne across Spain and Latin America.
-
C.
Lopez
Lopez is a municipality in the province of Quezon in the Philippines, known for its agricultural economy and coastal location.
-
D.
López-Gallego
López-Gallego is a Spanish surname most notably borne by film director Gonzalo López-Gallego, known for his work in thriller and science fiction cinema.
-
E.
Munoz-Flores
Munoz-Flores is the short name for the U.S. Supreme Court case United States v. Munoz-Flores, which addressed the constitutionality of certain federal monetary assessments under the Origination Clause.
- 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: Lopez-Fitzgerald Triple: [Theresa Lopez-Fitzgerald, familyName, Lopez-Fitzgerald]
Generated description
Lopez-Fitzgerald is the surname of a central working-class family featured in the American soap opera "Passions."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lopez-Fitzgerald Target entity description: Lopez-Fitzgerald is the surname of a central working-class family featured in the American soap opera "Passions."
-
A.
López-Salido
López-Salido is a Spanish surname most notably associated with economist J. David López-Salido, known for his work in macroeconomics and monetary policy.
-
B.
López
López is a common Spanish surname widely borne across Spain and Latin America.
-
C.
Lopez
Lopez is a municipality in the province of Quezon in the Philippines, known for its agricultural economy and coastal location.
-
D.
López-Gallego
López-Gallego is a Spanish surname most notably borne by film director Gonzalo López-Gallego, known for his work in thriller and science fiction cinema.
-
E.
Munoz-Flores
Munoz-Flores is the short name for the U.S. Supreme Court case United States v. Munoz-Flores, which addressed the constitutionality of certain federal monetary assessments under the Origination Clause.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15781d590819096f7361ca9736721 |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cfc8d08190a02abc90c889c8e1 |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc4ed71648190983a0a4150c4d8c4 |
completed | May 9, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc5a5b46881908589fd1dabef5378 |
completed | May 9, 2026, 11:39 p.m. |
Created at: April 10, 2026, 4:54 a.m.