Triple
T29585883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Saint-Gervais |
E754017
|
entity |
| Predicate | hasCityGovernmentNearby |
P92518
|
FINISHED |
| Object | Mairie de Paris |
—
|
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: Mairie de Paris | Statement: [Place Saint-Gervais, hasCityGovernmentNearby, Mairie de Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityGovernmentNearby Context triple: [Place Saint-Gervais, hasCityGovernmentNearby, Mairie de Paris]
-
A.
hasMunicipalGovernment
Indicates that an entity is administered or governed by a municipal-level governmental authority.
-
B.
hasMunicipalitySeatNearby
chosen
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
C.
hasCityGovernmentType
Indicates the specific form or structure of municipal governance that administers a city.
-
D.
hasNearbyCityFunction
Indicates that one entity serves as a nearby urban center or city-like service hub for another entity.
-
E.
hasLocalGovernmentBody
Indicates that an entity is administered or overseen by a specific local government authority or governing body.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f7117e55908190a67105e92bc4830f |
completed | May 3, 2026, 9:12 a.m. |
| PD | Predicate disambiguation | batch_69f70f380690819090cc34763ba460ed |
completed | May 3, 2026, 9:02 a.m. |
Created at: April 28, 2026, 6:10 p.m.