Triple
T362301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Zealand Sign Language |
E7882
|
entity |
| Predicate | languageFamily |
P1047
|
FINISHED |
| Object |
BANZSL
BANZSL is the family of closely related sign languages used in Britain, Australia, and New Zealand, sharing a common historical origin and many linguistic features.
|
E45831
|
NE FINISHED |
How this triple was built (4 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: BANZSL | Statement: [New Zealand Sign Language, languageFamily, BANZSL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BANZSL Context triple: [New Zealand Sign Language, languageFamily, BANZSL]
-
A.
BnG
BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
-
B.
BAL
BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
-
C.
BOL
BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
-
D.
Bun
Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
-
E.
Bauta
Bauta is a municipality in western Cuba known for its proximity to Havana and its mix of rural communities and small urban centers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BANZSL Triple: [New Zealand Sign Language, languageFamily, BANZSL]
Generated description
BANZSL is the family of closely related sign languages used in Britain, Australia, and New Zealand, sharing a common historical origin and many linguistic features.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BANZSL Target entity description: BANZSL is the family of closely related sign languages used in Britain, Australia, and New Zealand, sharing a common historical origin and many linguistic features.
-
A.
BnG
BnG is the commonly used abbreviation for Bòrd na Gàidhlig, the principal public body responsible for promoting and supporting the Scottish Gaelic language in Scotland.
-
B.
BAL
BAL is the Amtrak station code for Pennsylvania Station in Baltimore, Maryland, a major rail hub in the city’s transportation network.
-
C.
BOL
BOL is the three-letter ISO 3166-1 alpha-3 country code assigned to Bolivia.
-
D.
Bun
Bun is a modern, high-performance JavaScript runtime and toolkit designed as an alternative to Node.js and Deno, featuring a built-in bundler, test runner, and package manager.
-
E.
Bauta
Bauta is a municipality in western Cuba known for its proximity to Havana and its mix of rural communities and small urban centers.
- F. None of above. chosen
Provenance (5 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebcfb0f48190b9a9010c7837ac58 |
completed | Feb. 28, 2026, 1:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e57a56e081909004fcd7e15f457c |
completed | March 1, 2026, 7:06 a.m. |
| NEDg | Description generation | batch_69a3e5e50b848190ab5d036719048df8 |
completed | March 1, 2026, 7:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a3e63c749c8190b5bfd85b7ccafa9c |
completed | March 1, 2026, 7:09 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.