Triple
T7291094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapingamarangi language |
E164392
|
entity |
| Predicate | hasPronominalCategory |
P48360
|
FINISHED |
| Object | inclusive first person plural |
—
|
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: inclusive first person plural | Statement: [Kapingamarangi language, hasPronominalCategory, inclusive first person plural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPronominalCategory Context triple: [Kapingamarangi language, hasPronominalCategory, inclusive first person plural]
-
A.
hasPronounCategory
chosen
Indicates that an entity is associated with a specific category or type of pronoun (such as personal, possessive, reflexive, etc.).
-
B.
hasPronounSystem
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
-
C.
hasPronounForI
Indicates that an entity is associated with or uses a specific pronoun corresponding to the first-person singular "I" in a given language or context.
-
D.
hasPronounForIt
Indicates that one entity serves as the pronoun form referring to another entity.
-
E.
hasPreposition
Indicates that one entity is associated with or linked to another entity through a specific prepositional relationship.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6e8f3881908628b3d41aad70c6 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3 p.m.