Triple
T36712953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LR ĀM |
E906840
|
entity |
| Predicate | ĀMMeaningInLatvian |
P171056
|
FINISHED |
| Object | Ārlietu ministrija |
E906838
|
NE 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: Ārlietu ministrija | Statement: [LR ĀM, ĀMMeaningInLatvian, Ārlietu ministrija]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ĀMMeaningInLatvian Context triple: [LR ĀM, ĀMMeaningInLatvian, Ārlietu ministrija]
-
A.
lettersMeaning
Indicates that a set of letters or characters represents, signifies, or conveys a particular meaning or message.
-
B.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
-
C.
etMeaning
Indicates that one entity expresses or conveys the semantic content or intended sense of another entity (such as a word, phrase, or symbol).
-
D.
meaningInLanguage
chosen
Indicates that an expression or symbol has a particular meaning or interpretation within a specified language.
-
E.
ARMeaning
Indicates that an entity’s meaning, interpretation, or semantic content is being specified or defined in relation to another entity or context.
- F. None of above.
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_69f76e73ad108190a5241585f2303e9a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c8161dfc8190890b03483f8524c1 |
completed | May 3, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3a3833489c8190a93af45fb7f005fe |
completed | June 23, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.