Triple
T32210605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manuel Menéndez |
E822789
|
entity |
| Predicate | surnameVariantOf |
P16885
|
FINISHED |
| Object | Menendez (without accent) |
—
|
LITERAL 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: Menendez (without accent) | Statement: [Manuel Menéndez, surnameVariantOf, Menendez (without accent)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surnameVariantOf Context triple: [Manuel Menéndez, surnameVariantOf, Menendez (without accent)]
-
A.
surnameVariant
chosen
Indicates that one surname is an alternative spelling, form, or variation of another surname.
-
B.
nameHasVariant
Indicates that an entity’s name has an alternative or variant form.
-
C.
surnameUsedIn
Indicates that a particular surname is used or borne within a specified context, such as by a person, family, or group.
-
D.
surnameReversedFrom
Indicates that one entity’s surname is derived by reversing the character order of another entity’s surname.
-
E.
associatedSurname
Indicates that one entity has a surname that is linked or connected to another entity, such as a person, family, or name record.
- F. None of above.
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_69f3490a3bec819097bc58d4731b9d08 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb91c24481908bec766e2ed19345 |
completed | May 3, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:37 a.m.