Triple
T9034583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Cruz, Laguna |
E216458
|
entity |
| Predicate | primaryRegionalLanguage |
P1252
|
FINISHED |
| Object | Tagalog |
—
|
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: Tagalog | Statement: [Santa Cruz, Laguna, primaryRegionalLanguage, Tagalog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRegionalLanguage Context triple: [Santa Cruz, Laguna, primaryRegionalLanguage, Tagalog]
-
A.
primaryLanguageOf
chosen
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
B.
primaryLocalLanguageFamily
Indicates the main linguistic family to which the predominant local language of an entity belongs.
-
C.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
languageOfPrimaryCult
Indicates that a specified language is the main or dominant language used in a particular cult’s primary religious practices or rituals.
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6abf4af481908d21245332329d99 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.