Triple
T23051892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orsay-Ville station |
E574039
|
entity |
| Predicate | ticketSystem |
P25925
|
FINISHED |
| Object | Navigo |
—
|
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: Navigo | Statement: [Orsay-Ville station, ticketSystem, Navigo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Navigo Context triple: [Orsay-Ville station, ticketSystem, Navigo]
-
A.
Navigo
chosen
Navigo is the contactless smart card ticketing system used for public transportation across the Île-de-France region, including Paris.
-
B.
Navia
Navia is a coastal town and municipality in Asturias, northern Spain, known for its port, beaches, and role as a local commercial and tourist center.
-
C.
Amasra
Amasra is a historic coastal town and popular tourist destination on Turkey’s Black Sea coast, known for its scenic harbor, beaches, and ancient fortifications.
-
D.
Ussita
Ussita is a small mountain town in Italy’s Marche region, known for its location in the Sibillini Mountains and its traditional rural character.
-
E.
Maleva
Maleva is the wise Romani woman and mother of the original Wolf Man who serves as a mystical guide and bearer of the werewolf curse’s lore in Universal’s classic horror films.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245ba7ae48190be606dbc54120e39 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1867d010c8190bc5dba6758d0b797 |
completed | April 29, 2026, 4:18 a.m. |
Created at: April 17, 2026, 3:54 p.m.