Triple
T9561933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berthillon ice cream shop |
E230693
|
entity |
| Predicate | queueTypical |
P89799
|
FINISHED |
| Object | long lines in high season |
—
|
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: long lines in high season | Statement: [Berthillon ice cream shop, queueTypical, long lines in high season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: queueTypical Context triple: [Berthillon ice cream shop, queueTypical, long lines in high season]
-
A.
queueType
Indicates the classification or category of a queue that specifies how items in it are organized, prioritized, or processed.
-
B.
queueLocation
Indicates the place or position where an entity is arranged to wait in a queue or line.
-
C.
queueEntranceName
Indicates the name assigned to the entrance of a queue.
-
D.
queueInterface
Indicates that one entity serves as a queue interface through which another entity can enqueue, dequeue, or otherwise manage queued items or requests.
-
E.
queueLength
Indicates the current number of items or entities waiting in a queue.
- F. None of above. chosen
Provenance (4 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd994d31e08190b139f5ad10d8ea31 |
completed | April 1, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69ccd594d0ac8190a81bc11a3a538167 |
completed | April 1, 2026, 8:21 a.m. |
| PDg | Predicate description generation | batch_69ccd93e90048190a2b0d7c5c195ba98 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:03 p.m.