Triple
T771623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Megleno-Romanian |
E16291
|
entity |
| Predicate | hasISOCodeType |
P18994
|
FINISHED |
| Object | ISO 639-3 |
—
|
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: ISO 639-3 | Statement: [Megleno-Romanian, hasISOCodeType, ISO 639-3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISOCodeType Context triple: [Megleno-Romanian, hasISOCodeType, ISO 639-3]
-
A.
hasISOCode
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
B.
hasISO6393Code
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
-
C.
previousISOCode
Indicates that an entity was formerly identified by a different ISO code before its current one.
-
D.
ISOCode
Indicates that an entity is associated with a specific standardized code defined by the International Organization for Standardization (ISO).
-
E.
hasAirportCodeType
Indicates that an airport code is associated with a specific classification or type (e.g., IATA, ICAO, FAA).
- F. None of above. chosen
Provenance (4 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a706abf88190a1cbc2dfbbf9968a |
completed | March 1, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69a4a508c42c8190850a0ac7844a3ea9 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5a35c68819082429755c046e9a7 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.