Triple
T31122062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archevêché de Paris |
E793247
|
entity |
| Predicate | previousOrdinary |
P196328
|
FINISHED |
| Object | Michel Aupetit |
—
|
NE NERFINISHED |
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: Michel Aupetit | Statement: [Archevêché de Paris, previousOrdinary, Michel Aupetit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousOrdinary Context triple: [Archevêché de Paris, previousOrdinary, Michel Aupetit]
-
A.
pastOrdinary
Indicates that the related action or state occurred in the past using the simple (non-progressive, non-perfect) tense.
-
B.
currentOrdinary
Indicates that an entity currently holds or is in the state of an ordinary (non-special or non-exceptional) status or role.
-
C.
firstOrdinary
Indicates that the subject is the first entity to hold or occupy an ordinary (non-special, standard) position, role, or status in a given sequence or context.
-
D.
usesOrdinary
Indicates that one entity makes use of another entity in a standard, non-specialized, or typical manner.
-
E.
ordinary
Indicates that something or someone is typical, usual, or not special or exceptional in the relevant context.
- 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_69f224d0a7688190af3fe3e6e26d01ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe21b0cba48190b56c39e9f1c0eafa |
completed | May 8, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69fe204576848190aecf204e2adba5dc |
completed | May 8, 2026, 5:41 p.m. |
| PDg | Predicate description generation | batch_69fe21afdc4c8190913ac4b55a9a5f52 |
completed | May 8, 2026, 5:47 p.m. |
Created at: April 29, 2026, 9:04 p.m.