Triple
T16697441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IN-HR |
E405750
|
entity |
| Predicate | hasLanguageCodeFormat |
P124284
|
FINISHED |
| Object | alpha-numeric |
—
|
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: alpha-numeric | Statement: [IN-HR, hasLanguageCodeFormat, alpha-numeric]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageCodeFormat Context triple: [IN-HR, hasLanguageCodeFormat, alpha-numeric]
-
A.
hasLinguisticCode
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
-
B.
hasLanguageCodeScope
Indicates that a language code is valid or applicable only within a specified scope, context, or domain.
-
C.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
D.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
E.
hasISO15924Number
Indicates that an entity (a writing script) is associated with a specific numeric code defined by the ISO 15924 standard.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3832e93c48190a594c498e9cc901a |
completed | April 18, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69e319bc73908190a0e38bc926b31f10 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.