Triple
T5635810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toqabaqita |
E147944
|
entity |
| Predicate | hasPronounSystemFeature |
P26817
|
FINISHED |
| Object | inclusive-exclusive contrast |
—
|
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-exclusive contrast | Statement: [Toqabaqita, hasPronounSystemFeature, inclusive-exclusive contrast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPronounSystemFeature Context triple: [Toqabaqita, hasPronounSystemFeature, inclusive-exclusive contrast]
-
A.
hasPronounSystem
chosen
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
-
B.
hasPronounCategory
Indicates that an entity is associated with a specific category or type of pronoun (such as personal, possessive, reflexive, etc.).
-
C.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
D.
hasPronounForIt
Indicates that one entity serves as the pronoun form referring to another entity.
-
E.
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.
- 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_69c00907bc8881909ed760d3ed73ef35 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0226286208190b6ccf036cc09fe82 |
completed | March 22, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69c01b1f12ec8190b4b9d9ee31cabe19 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:41 p.m.