Triple
T15042595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citadis 403 |
E378637
|
entity |
| Predicate | passengerArea |
P30403
|
FINISHED |
| Object | single-level interior |
—
|
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: single-level interior | Statement: [Citadis 403, passengerArea, single-level interior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerArea Context triple: [Citadis 403, passengerArea, single-level interior]
-
A.
hasPassengerArea
chosen
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
-
B.
passengerAccess
Indicates that a passenger is allowed to enter, use, or move through a particular vehicle, area, or transportation-related facility.
-
C.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
D.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
E.
passengerSystem
Indicates a relationship where an entity functions as or belongs to a passenger-related system (such as a transport or service system designed for passengers).
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82f73208190bb55fa6b20074e27 |
completed | April 15, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69de9a69d7848190b2b4662dd30f20e9 |
completed | April 14, 2026, 7:50 p.m. |
Created at: April 10, 2026, 3 a.m.