Triple
T2120895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greg Abbott |
E43918
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Cecilia Abbott
Cecilia Abbott is an American educator and the First Lady of Texas, married to Governor Greg Abbott.
|
E237729
|
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: Cecilia Abbott | Statement: [Greg Abbott, spouse, Cecilia Abbott]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cecilia Abbott Context triple: [Greg Abbott, spouse, Cecilia Abbott]
-
A.
Laura Kelly
Laura Kelly is an American Democratic politician serving as the governor of Kansas.
-
B.
Janai Nelson
Janai Nelson is a civil rights attorney and legal scholar who serves as the president and director-counsel of the NAACP Legal Defense and Educational Fund, one of the United States’ leading racial justice organizations.
-
C.
Hochuli
Hochuli is a surname most prominently associated with Ed Hochuli, a well-known former NFL referee recognized for his detailed penalty explanations and muscular physique.
-
D.
Tina Kotek
Tina Kotek is an American politician and former state legislative leader who became the first openly lesbian governor in the United States.
-
E.
Kim Brown
Kim Brown is the central protagonist of "The Unit," around whom the story’s events and character dynamics primarily revolve.
- 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: Cecilia Abbott Triple: [Greg Abbott, spouse, Cecilia Abbott]
Generated description
Cecilia Abbott is an American educator and the First Lady of Texas, married to Governor Greg Abbott.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cecilia Abbott Target entity description: Cecilia Abbott is an American educator and the First Lady of Texas, married to Governor Greg Abbott.
-
A.
Laura Kelly
Laura Kelly is an American Democratic politician serving as the governor of Kansas.
-
B.
Janai Nelson
Janai Nelson is a civil rights attorney and legal scholar who serves as the president and director-counsel of the NAACP Legal Defense and Educational Fund, one of the United States’ leading racial justice organizations.
-
C.
Hochuli
Hochuli is a surname most prominently associated with Ed Hochuli, a well-known former NFL referee recognized for his detailed penalty explanations and muscular physique.
-
D.
Tina Kotek
Tina Kotek is an American politician and former state legislative leader who became the first openly lesbian governor in the United States.
-
E.
Kim Brown
Kim Brown is the central protagonist of "The Unit," around whom the story’s events and character dynamics primarily revolve.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb3404348190bc843022fbd2b4d0 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5197259c8190bffbbb4abaaddfd0 |
completed | March 9, 2026, 4:50 a.m. |
| NEDg | Description generation | batch_69ae532d39d8819097ae5826b42f92b2 |
completed | March 9, 2026, 4:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae539f7f008190b5f9d15fb3d362d9 |
completed | March 9, 2026, 4:59 a.m. |
Created at: March 4, 2026, 7:44 p.m.