Triple
T36391513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coria del Río |
E896339
|
entity |
| Predicate | hasSurnameTradition |
P201686
|
FINISHED |
| Object | Descendants with surname Japón |
—
|
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: Descendants with surname Japón | Statement: [Coria del Río, hasSurnameTradition, Descendants with surname Japón]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurnameTradition Context triple: [Coria del Río, hasSurnameTradition, Descendants with surname Japón]
-
A.
hasTraditionalName
Indicates that an entity is associated with a name traditionally used or recognized for it, often rooted in long-standing cultural or historical practice.
-
B.
hasBaseSurname
Indicates that an entity’s surname is derived from, or fundamentally corresponds to, a specified base or canonical surname.
-
C.
hasSeptSurname
Indicates that an entity bears a surname associated with a particular sept (a family subgroup or clan division).
-
D.
hasSurnamePrefix
Indicates that one entity’s surname begins with, or is prefixed by, the string or component specified by the other entity.
-
E.
hasSurnameType
Indicates that an entity’s surname belongs to a particular category or type (e.g., patronymic, toponymic, occupational).
- F. None of above. chosen
Provenance (4 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_69f76e52e3108190becf70b090ae7bd6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a00144238708190acbec3f791cc873e |
completed | May 10, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_6a00120244a4819090ef39070aba9d99 |
completed | May 10, 2026, 5:05 a.m. |
| PDg | Predicate description generation | batch_6a001440a26c81908ba50779bb6e1679 |
completed | May 10, 2026, 5:14 a.m. |
Created at: May 3, 2026, 4:10 p.m.