Triple
T19906197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malta Dockyard |
E478422
|
entity |
| Predicate | languageOfLocalWorkforce |
P11430
|
FINISHED |
| Object | Maltese |
—
|
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: Maltese | Statement: [Malta Dockyard, languageOfLocalWorkforce, Maltese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalWorkforce Context triple: [Malta Dockyard, languageOfLocalWorkforce, Maltese]
-
A.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
B.
languageOfMajorityEligibleWorks
Indicates the primary language in which most of the qualifying or eligible works in a given set are produced or available.
-
C.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
D.
majorityLanguageOf
chosen
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
E.
laborForceCharacteristic
Indicates a relationship where an entity is described or classified by a specific attribute or status related to its participation in the labor force.
- 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_69d8e520682081909892916424699bd5 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65946916881909c3f52208c07aa64 |
completed | April 20, 2026, 4:50 p.m. |
| PD | Predicate disambiguation | batch_69e537ecda248190895c96afb6243823 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.