Triple
T15092267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glacière |
E360447
|
entity |
| Predicate | hasStaffedBooths |
P41426
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Glacière, hasStaffedBooths, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffedBooths Context triple: [Glacière, hasStaffedBooths, yes]
-
A.
hasCollectorBooth
Indicates that an entity has an associated collector booth, typically a designated place or station where collection-related activities (such as payments, tickets, or items) are handled.
-
B.
hasStaffedHours
Indicates that specific hours or time periods are assigned during which staff are present and available.
-
C.
hasStaffedTicketOffice
chosen
Indicates that a location or facility has a ticket office that is staffed by personnel.
-
D.
hasOnsiteActivity
Indicates that an entity conducts or participates in activities that physically take place at a specific site or location.
-
E.
hasExhibitors
Indicates that an entity includes, hosts, or is associated with one or more exhibitors.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027925788190b955fdc6626adf7d |
completed | April 15, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:04 a.m.