Triple
T1655968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michel-Antoine David |
E35799
|
entity |
| Predicate | roleInProduction |
P268
|
FINISHED |
| Object | publisher of the Encyclopédie |
—
|
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: publisher of the Encyclopédie | Statement: [Michel-Antoine David, roleInProduction, publisher of the Encyclopédie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInProduction Context triple: [Michel-Antoine David, roleInProduction, publisher of the Encyclopédie]
-
A.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
B.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
C.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
D.
role
chosen
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
-
E.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69a907cff53c8190b424f088478d3e2c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:29 p.m.