Triple
T29194735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcelino |
E740093
|
entity |
| Predicate | hasNameDayTraditionRegion |
P8953
|
FINISHED |
| Object | Spanish-speaking countries |
—
|
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: Spanish-speaking countries | Statement: [Marcelino, hasNameDayTraditionRegion, Spanish-speaking countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameDayTraditionRegion Context triple: [Marcelino, hasNameDayTraditionRegion, Spanish-speaking countries]
-
A.
hasNameDayInSomeCountriesFor
Indicates that an entity is celebrated with a name day, in at least some countries, on behalf of or in relation to another specified entity.
-
B.
hasNameDayInformation
Indicates that there exists associated information about a person’s name day, such as the date or related observances.
-
C.
nameDayRegion
chosen
Indicates the region or geographic area in which a particular name day is observed or recognized.
-
D.
hasRegionalHolidayName
Indicates that a regional holiday is associated with a specific name or designation used to refer to it.
-
E.
hasNameDayOrReligiousUsage
Indicates that an entity has an associated name day celebration or is used in a religious or liturgical context.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: April 28, 2026, 12:03 p.m.