Triple
T10928825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laumière |
E258144
|
entity |
| Predicate | ticketingArea |
P43373
|
FINISHED |
| Object | underground concourse |
—
|
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: underground concourse | Statement: [Laumière, ticketingArea, underground concourse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingArea Context triple: [Laumière, ticketingArea, underground concourse]
-
A.
ticketingLocation
chosen
Indicates the place or point where tickets are issued, sold, or otherwise processed for an event, service, or journey.
-
B.
ticketingScope
Indicates the range or domain within which ticketing actions (such as creation, assignment, or management of tickets) are valid or applicable.
-
C.
ticketAcceptanceArea
Indicates the geographic or operational area within which a given ticket is valid for use or accepted as proof of payment.
-
D.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
-
E.
ticketingIssue
Indicates that there is a problem, error, or complication related to a ticketing process or ticket-based system.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7709eb0ec819093f7d3f99097bbe4 |
completed | April 9, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69d72e799f808190b6ab64fc7586a303 |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:22 p.m.