Triple
T16745576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corpus de Referencia del Español Actual |
E406942
|
entity |
| Predicate | acronym |
P43
|
FINISHED |
| Object | CREA |
E403329
|
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: CREA | Statement: [Corpus de Referencia del Español Actual, acronym, CREA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CREA Context triple: [Corpus de Referencia del Español Actual, acronym, CREA]
-
A.
CREA
chosen
CREA is a large reference corpus of contemporary Spanish used for linguistic research and language analysis.
-
B.
CREI
CREI is a Barcelona-based research institute specializing in macroeconomics and international economics, closely linked to academic institutions such as Universitat Pompeu Fabra.
-
C.
Create
Create is an American public television multicast network focused on how-to and lifestyle programming, including cooking, travel, home improvement, and crafts.
-
D.
Create
Create is a programmable mobile robot platform developed by iRobot, widely used for education, research, and hobbyist robotics projects.
-
E.
Let’s Create
Let’s Create is Arts Council England’s 10-year strategy that sets out a vision and priorities for supporting arts, culture, and creativity across England.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa223aa88190a3c1805ece7317e2 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52033748190ae207d72d437236b |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.