Triple
T1394166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | René |
E30626
|
entity |
| Predicate | pronunciationLanguage |
P27691
|
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: [René, pronunciationLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pronunciationLanguage Context triple: [René, pronunciationLanguage, French]
-
A.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
D.
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.
-
E.
hasStandardPronunciationBasedOn
Indicates that one entity’s standard or canonical pronunciation is determined or derived from another entity’s pronunciation.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c37cd99081908d16014e0b99992d |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c13270d8819081d8ee1be34cabf5 |
completed | March 1, 2026, 10:44 p.m. |
Created at: March 1, 2026, 7:59 p.m.