Triple
T13825200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLIPSAS |
E332231
|
entity |
| Predicate | hasAbbreviationOriginLanguage |
P43870
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [CLIPSAS, hasAbbreviationOriginLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAbbreviationOriginLanguage Context triple: [CLIPSAS, hasAbbreviationOriginLanguage, French]
-
A.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
-
B.
hasAcronymExpansionLanguage
chosen
Indicates that a specified language is the language in which an acronym’s full expansion is expressed.
-
C.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
D.
hasAbbreviationStatus
Indicates that an entity has a particular status or condition regarding its abbreviation (e.g., whether it is abbreviated, how, or to what extent).
-
E.
indirectOriginLanguage
Indicates that something originates from a particular language, not directly but through one or more intermediate languages or sources.
- F. None of above.
Provenance (3 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0285fb7c8190be4b90bdc0d6fa53 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.