Triple
T9796513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018 Texas gubernatorial election |
E237730
|
entity |
| Predicate | runnerUp |
P2683
|
FINISHED |
| Object |
Lupe Valdez
Lupe Valdez is an American politician and former Dallas County sheriff who became the Democratic nominee for governor of Texas in 2018.
|
E821361
|
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: Lupe Valdez | Statement: [2018 Texas gubernatorial election, runnerUp, Lupe Valdez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lupe Valdez Context triple: [2018 Texas gubernatorial election, runnerUp, Lupe Valdez]
-
A.
Lumi Cavazos
Lumi Cavazos is a Mexican actress best known internationally for her acclaimed role in the film "Like Water for Chocolate."
-
B.
Julia Carin Cavazos
Julia Carin Cavazos, known professionally as Julia Michaels, is an American singer-songwriter recognized for her solo pop hits and for writing chart-topping songs for numerous major artists.
-
C.
Laura Kelly
Laura Kelly is an American Democratic politician serving as the governor of Kansas.
-
D.
Drue Gensler
Drue Gensler is an American architect and business leader best known as a co-founder of the global architecture and design firm Gensler.
-
E.
Lauro Cavazos
Lauro Cavazos was the first Hispanic U.S. Secretary of Education, serving under Presidents Ronald Reagan and George H. W. Bush.
- 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: Lupe Valdez Triple: [2018 Texas gubernatorial election, runnerUp, Lupe Valdez]
Generated description
Lupe Valdez is an American politician and former Dallas County sheriff who became the Democratic nominee for governor of Texas in 2018.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lupe Valdez Target entity description: Lupe Valdez is an American politician and former Dallas County sheriff who became the Democratic nominee for governor of Texas in 2018.
-
A.
Lumi Cavazos
Lumi Cavazos is a Mexican actress best known internationally for her acclaimed role in the film "Like Water for Chocolate."
-
B.
Julia Carin Cavazos
Julia Carin Cavazos, known professionally as Julia Michaels, is an American singer-songwriter recognized for her solo pop hits and for writing chart-topping songs for numerous major artists.
-
C.
Laura Kelly
Laura Kelly is an American Democratic politician serving as the governor of Kansas.
-
D.
Drue Gensler
Drue Gensler is an American architect and business leader best known as a co-founder of the global architecture and design firm Gensler.
-
E.
Lauro Cavazos
Lauro Cavazos was the first Hispanic U.S. Secretary of Education, serving under Presidents Ronald Reagan and George H. W. Bush.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda34a53548190a8cb524381fe2bf9 |
completed | April 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c43fdfec8190b7115a680c79d702 |
completed | April 5, 2026, 2:09 a.m. |
| NEDg | Description generation | batch_69d1c4d62a78819089ece2bb1f5fb66b |
completed | April 5, 2026, 2:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1c589b90481908bc0944868d648b2 |
completed | April 5, 2026, 2:14 a.m. |
Created at: March 30, 2026, 8:28 p.m.