Triple
T10635451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaragoza, Nuevo León |
E250567
|
entity |
| Predicate | isNamedForOccupationOfHonouree |
P24365
|
FINISHED |
| Object | Mexican general |
—
|
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: Mexican general | Statement: [Zaragoza, Nuevo León, isNamedForOccupationOfHonouree, Mexican general]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedForOccupationOfHonouree Context triple: [Zaragoza, Nuevo León, isNamedForOccupationOfHonouree, Mexican general]
-
A.
isNamedAfterOccupation
Indicates that an entity’s name is derived from or based on a particular occupation or profession.
-
B.
namedForNationalityOfHonouree
Indicates that something is named in honor of a person, specifically referencing that person's nationality.
-
C.
isNamedForEponymRole
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
D.
hasAwardNamedAfter
Indicates that an entity has an award that is named in honor of another entity.
-
E.
isNamedFor
chosen
Indicates that one entity bears its name in honor of, or derived from, another entity.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfac70f481908363f9ac0b651fbe |
completed | April 8, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69d6dd83b114819098e84dc658e82d7e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:03 p.m.