Triple
T4734565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chancellerie des universités de Paris |
E105091
|
entity |
| Predicate | coordinatesPlace |
P1573
|
FINISHED |
| Object | certain inter-university services in Paris |
—
|
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: certain inter-university services in Paris | Statement: [Chancellerie des universités de Paris, coordinatesPlace, certain inter-university services in Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coordinatesPlace Context triple: [Chancellerie des universités de Paris, coordinatesPlace, certain inter-university services in Paris]
-
A.
coordinateLocation
chosen
Indicates that an entity is located at, or associated with, a specific geographic coordinate or set of coordinates.
-
B.
streetLocation
Indicates that one entity is located on, along, or at a specific street associated with the other entity.
-
C.
mapLocation
Indicates a relationship where an entity is associated with a specific position or area on a map.
-
D.
propertyLocation
Indicates the geographical place or address where a property is situated or found.
-
E.
locationDetail
Indicates a more specific or refined description of a location associated with an entity or event.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6467a1fc819089485b4d76e0edc4 |
completed | March 20, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69bd6221c3b881908604f35f8de6f16b |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.