Triple
T28330677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ménilmontant |
E717529
|
entity |
| Predicate | integratedIntoParis |
P170661
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Ménilmontant, integratedIntoParis, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: integratedIntoParis Context triple: [Ménilmontant, integratedIntoParis, 19th century]
-
A.
integratedIntoQuebecCity
Indicates that one entity has been incorporated or merged into the administrative or territorial structure of Quebec City.
-
B.
succeededByAsCountOfParis
Indicates that one entity is followed or replaced by another in a sequence or count specifically related to Paris.
-
C.
yearMovedToParis
Indicates the year in which an entity moved to Paris.
-
D.
locatedInMetropolitanFrance
Indicates that the subject is geographically situated within the territory of metropolitan (continental) France.
-
E.
precededByAsCountOfParis
Indicates that one event, action, or state occurs immediately before another, specifically in the context of being counted or enumerated as an instance related to Paris.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f693ffa7908190aa4c451b16df9be6 |
completed | May 3, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 28, 2026, 12:32 a.m.