Triple
T224817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haiti |
E4291
|
entity |
| Predicate | nationalMottoLanguage |
P4406
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Haiti, nationalMottoLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalMottoLanguage Context triple: [Haiti, nationalMottoLanguage, French]
-
A.
languageOfMotto
chosen
Indicates the language in which a motto is written or expressed.
-
B.
isStateMottoOf
Indicates that a phrase or sentence serves as the official state motto of a particular state.
-
C.
officialLanguageOnFlag
Indicates that a particular language is officially represented in the text or inscriptions displayed on a flag.
-
D.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
E.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b5739dc8190bad8bfa330ce0499 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.