Triple
T18458501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | École Normale Supérieure de Rennes |
E450966
|
entity |
| Predicate | isInCityType |
P121869
|
FINISHED |
| Object | university city |
—
|
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: university city | Statement: [École Normale Supérieure de Rennes, isInCityType, university city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInCityType Context triple: [École Normale Supérieure de Rennes, isInCityType, university city]
-
A.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
-
B.
belongsToCityType
chosen
Indicates that one entity is classified under, or associated with, a particular type or category of city.
-
C.
isFirstOfTypeInCity
Indicates that an entity is the earliest or original instance of its particular type to exist or be established within a given city.
-
D.
isUrbanAreaOfType
Indicates that a given area is classified as belonging to a specific type or category of urban area (e.g., city, town, suburb).
-
E.
isCityOf
Indicates that one entity is a city that belongs to, is located within, or is administratively part of another entity (such as a country, state, or region).
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a7c18d88190ac17f58111722223 |
completed | April 19, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:31 a.m.