Triple
T5092801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miquel |
E114791
|
entity |
| Predicate | hasEquivalentName |
P3889
|
FINISHED |
| Object | Mikel |
E114789
|
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: Mikel | Statement: [Miquel, hasEquivalentName, Mikel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikel Context triple: [Miquel, hasEquivalentName, Mikel]
-
A.
Mikel
chosen
Mikel is a given name, commonly a variant of Michael used in various cultures, particularly in Basque and Spanish-speaking regions.
-
B.
Mikel Adams
Mikel Adams is an individual whose name is an alternative spelling variant of Michael Adams.
-
C.
Arteta
Arteta is a Spanish former professional footballer and current football manager best known for managing Arsenal in the English Premier League.
-
D.
Álvaro
Álvaro is a masculine given name of Spanish origin commonly used in Spain and Latin America.
-
E.
Renaldo
Renaldo is the titular character in Bob Dylan’s 1978 film "Renaldo and Clara," a surreal, semi-autobiographical drama blending concert footage with fictional vignettes.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd754369708190bf4e171a904a19e1 |
completed | March 20, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb14f097081908d835190f13796dd |
completed | March 21, 2026, 2:55 p.m. |
Created at: March 20, 2026, 1:40 p.m.