Triple
T17972226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Île-de-France rail network |
E449374
|
entity |
| Predicate | includesSystem |
P1393
|
FINISHED |
| Object | CDGVAL |
—
|
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: CDGVAL | Statement: [Île-de-France rail network, includesSystem, CDGVAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CDGVAL Context triple: [Île-de-France rail network, includesSystem, CDGVAL]
-
A.
CDGVAL
chosen
CDGVAL is the automated light-rail shuttle system that links the terminals and key facilities within Paris Charles de Gaulle Airport.
-
B.
CDG
CDG is the IATA airport code for Charles de Gaulle Airport, the main international airport serving Paris and one of Europe’s busiest air hubs.
-
C.
CGD
CGD is the IATA airport code for Changde Taohuayuan Airport in Changde, Hunan Province, China.
-
D.
CGR
CGR is the IATA airport code for Campo Grande International Airport in Campo Grande, Brazil.
-
E.
GDEcD
GDEcD is the U.S. state of Georgia’s lead agency for promoting economic development, including business recruitment, trade, tourism, and film and entertainment industries.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fb58c481909726d6f916f6f646 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.