Triple
T7696088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Executive Minister of Iglesia ni Cristo |
E174372
|
entity |
| Predicate | languageOfAlternativeLabel |
P63334
|
FINISHED |
| Object | Filipino |
—
|
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: Filipino | Statement: [Executive Minister of Iglesia ni Cristo, languageOfAlternativeLabel, Filipino]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAlternativeLabel Context triple: [Executive Minister of Iglesia ni Cristo, languageOfAlternativeLabel, Filipino]
-
A.
alternateLanguageName
chosen
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
B.
languageOfAlternativeTitle
Indicates the language in which an alternative or variant title of an entity is expressed.
-
C.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
-
D.
languageOfVariant
Indicates that one entity is the language in which a particular variant or version of another entity is expressed.
-
E.
languageOfProduct
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:03 p.m.