Triple
T5659238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcelo Suárez-Orozco |
E124694
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Marcelo Suárez-Orozco |
E124694
|
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: Marcelo Suárez-Orozco | Statement: [Marcelo Suárez-Orozco, name, Marcelo Suárez-Orozco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marcelo Suárez-Orozco Context triple: [Marcelo Suárez-Orozco, name, Marcelo Suárez-Orozco]
-
A.
Marcelo Suárez-Orozco
chosen
Marcelo Suárez-Orozco is a prominent scholar of immigration and education who serves as a higher-education leader in the United States.
-
B.
Sabina Alkire
Sabina Alkire is a development economist known for her pioneering work on multidimensional poverty measurement and co-creating the global Multidimensional Poverty Index.
-
C.
Saskia Sassen
Saskia Sassen is a prominent sociologist best known for her work on globalization, migration, and the concept of the global city.
-
D.
J. David López-Salido
J. David López-Salido is an economist known for his coauthored research in macroeconomics and monetary policy, including work with Jordi Galí.
-
E.
Jorge A. Jimenez
Jorge A. Jimenez is an actor known for his role in the action drama film "Mercury Plains."
- 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_69c0082774a481909d7e63fb2aad56ac |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c0231e3c388190a2dd2c59b4a25881 |
completed | March 22, 2026, 5:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04da37ffc819095f33e7e66e7c1d0 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.