Triple
T2012662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 101st Airborne Museum Le Mess |
E43722
|
entity |
| Predicate | languageOfInformation |
P31857
|
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: [101st Airborne Museum Le Mess, languageOfInformation, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfInformation Context triple: [101st Airborne Museum Le Mess, languageOfInformation, French]
-
A.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
B.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
D.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
E.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b2ed6c8190ad51f0af90db2a02 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.