Triple
T17123370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue du Général-Lemonnier |
E415523
|
entity |
| Predicate | hasTouristicSignificance |
P94116
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Avenue du Général-Lemonnier, hasTouristicSignificance, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristicSignificance Context triple: [Avenue du Général-Lemonnier, hasTouristicSignificance, yes]
-
A.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
B.
hasTouristSignage
Indicates that there is official signage present to guide or inform tourists about a place, route, or attraction.
-
C.
hasTourismPotential
chosen
Indicates that a place or resource possesses qualities that make it attractive or suitable for tourism activities or development.
-
D.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
-
E.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80b7e6881909f7635875549a2f1 |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6d20808190a38bb32e2294bc48 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:36 a.m.