Triple
T15390739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty Suarez |
E368036
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Suarez |
E660187
|
NE FINISHED |
How this triple was built (2 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: Suarez | Statement: [Betty Suarez, familyName, Suarez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suarez Context triple: [Betty Suarez, familyName, Suarez]
-
A.
Suárez
chosen
Suárez is a common Spanish-language surname borne by numerous notable figures across politics, sports, arts, and literature in the Hispanic world.
-
B.
Suárez
Suárez is a municipality in Colombia, likely located near Flandes in the Tolima region.
-
C.
Justin Suarez
Justin Suarez is a fashion-loving, openly gay teenager and the supportive nephew of protagonist Betty Suarez on the television series "Ugly Betty."
-
D.
Flody Suarez
Flody Suarez is an American television and theater producer known for his work on projects such as the Broadway musical "The Cher Show."
-
E.
Luis Suárez
Luis Suárez is a prolific Uruguayan striker renowned for his goal-scoring exploits at clubs such as Ajax, Liverpool, and Barcelona, as well as for his controversial on-field incidents.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7727a081908eff45bbc1633c8a |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff134e37d881909f373b90a99fc067 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:19 a.m.