Triple
T23177339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laínez |
E579039
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Laynez |
—
|
NE NERFINISHED |
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: Laynez | Statement: [Laínez, hasVariantSpelling, Laynez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laynez Context triple: [Laínez, hasVariantSpelling, Laynez]
-
A.
Laynez
chosen
Laynez is a variant spelling of the Spanish surname Laínez, historically associated with figures such as Diego Laínez, a prominent 16th-century Jesuit.
-
B.
Layana
Layana is a small municipality located in the Cinco Villas comarca of the province of Zaragoza in Aragon, northeastern Spain.
-
C.
Ellzey
Ellzey is a surname most notably associated with Jake Ellzey, a U.S. politician and former Navy fighter pilot serving as a congressman from Texas.
-
D.
Laino
Laino is a small Italian municipality located in the Valle d’Intelvi area of the Lombardy region, near Lake Como.
-
E.
Eligh
Eligh is an American underground hip hop artist and producer best known as a member of the Living Legends collective and for his prolific solo and collaborative work.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fd2a388190b814c0dfa15f7148 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f6b823c8190a2d39c54e48a1001 |
completed | April 29, 2026, 4:56 a.m. |
Created at: April 17, 2026, 4:04 p.m.