Triple
T16289017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Île-de-France fare system |
E395467
|
entity |
| Predicate | includesProduct |
P3585
|
FINISHED |
| Object | Navigo Mois |
E227653
|
NE 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: Navigo Mois | Statement: [Île-de-France fare system, includesProduct, Navigo Mois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Navigo Mois Context triple: [Île-de-France fare system, includesProduct, Navigo Mois]
-
A.
Navigo
chosen
Navigo is the contactless smart card ticketing system used for public transportation across the Île-de-France region, including Paris.
-
B.
Nauta
Nauta is a small river port town in Peru’s Loreto region, serving as a key gateway for tourism and access to the Pacaya-Samiria National Reserve in the Amazon rainforest.
-
C.
Marina
Marina is a recurring comedic character in the long-running British sitcom "Last of the Summer Wine," known for her flirtatious relationship with the married Howard.
-
D.
Marina
Marina is the given name of Marina von Neumann Whitman, an American economist and former General Motors executive.
-
E.
Marina
Marina is a female given name of Latin origin, commonly used in various cultures and often associated with the sea.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e249165af881908ce44c4517c93c12 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025fd56008190a9cb896e7ea2d26a |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:05 a.m.