Triple
T2344065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Romo |
E45090
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Romo
Romo is a surname most prominently associated with former Dallas Cowboys quarterback and current NFL broadcaster Tony Romo.
|
E260344
|
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: Romo | Statement: [Tony Romo, familyName, Romo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romo Context triple: [Tony Romo, familyName, Romo]
-
A.
Hector Williams
Hector Williams is a key member of the elite counterterrorism team in the television series "The Unit," known for his courage, tactical skill, and strong moral compass.
-
B.
Rasool Diaz
Rasool Diaz is a songwriter best known for co-writing the hit Beyoncé and Jay-Z track "Drunk in Love."
-
C.
Tully Marshall
Tully Marshall was an American character actor of the silent and early sound film era, known for his prolific work in supporting roles across numerous Hollywood productions.
-
D.
Roderic Dallas
Roderic Dallas was a distinguished Australian fighter ace of World War I who became one of the leading pilots in British naval aviation.
-
E.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
- 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: Romo Triple: [Tony Romo, familyName, Romo]
Generated description
Romo is a surname most prominently associated with former Dallas Cowboys quarterback and current NFL broadcaster Tony Romo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Romo Target entity description: Romo is a surname most prominently associated with former Dallas Cowboys quarterback and current NFL broadcaster Tony Romo.
-
A.
Hector Williams
Hector Williams is a key member of the elite counterterrorism team in the television series "The Unit," known for his courage, tactical skill, and strong moral compass.
-
B.
Rasool Diaz
Rasool Diaz is a songwriter best known for co-writing the hit Beyoncé and Jay-Z track "Drunk in Love."
-
C.
Tully Marshall
Tully Marshall was an American character actor of the silent and early sound film era, known for his prolific work in supporting roles across numerous Hollywood productions.
-
D.
Roderic Dallas
Roderic Dallas was a distinguished Australian fighter ace of World War I who became one of the leading pilots in British naval aviation.
-
E.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6afe38c81909deb1de2a1c4eda9 |
completed | March 7, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea88113988190b89abfc01f5bf6f4 |
completed | March 9, 2026, 11:01 a.m. |
| NEDg | Description generation | batch_69aeaacdb19081908561e845eda30143 |
completed | March 9, 2026, 11:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aeab435b7081909ec4815f64fe9ea1 |
completed | March 9, 2026, 11:13 a.m. |
Created at: March 4, 2026, 7:52 p.m.