Triple
T38694793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beti-Fang |
E949967
|
entity |
| Predicate | hasISO6391CodeForMember |
P191661
|
FINISHED |
| Object | fan |
—
|
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: fan | Statement: [Beti-Fang, hasISO6391CodeForMember, fan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISO6391CodeForMember Context triple: [Beti-Fang, hasISO6391CodeForMember, fan]
-
A.
haveISO639Code
Indicates that a language or linguistic entity is associated with a specific ISO 639 standardized language code.
-
B.
hasISO6393Code
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
-
C.
hasISO639Type
Indicates the classification of a language resource according to its ISO 639 code type (e.g., ISO 639-1, 639-2, 639-3).
-
D.
hasISO639LanguageCodeForMajorLanguage
Indicates that an entity is associated with a primary or major language identified by a specific ISO 639 language code.
-
E.
hasISO639MacrolanguageCode
Indicates that a language entity is associated with a specific ISO 639 macrolanguage code that represents a broader language grouping.
- 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_69f76f0124408190bb39c3040734846b |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fce545fec881909247a3af821d21ae |
completed | May 7, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69fce12eaeec81908cf81346b2cef6e0 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce54532948190a5cfacfe18e09322 |
completed | May 7, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:33 p.m.