Triple
T3768629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schneider Electric Marathon de Paris |
E82740
|
entity |
| Predicate | hasCutoffTime |
P51012
|
FINISHED |
| Object | time limit for completion |
—
|
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: time limit for completion | Statement: [Schneider Electric Marathon de Paris, hasCutoffTime, time limit for completion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCutoffTime Context triple: [Schneider Electric Marathon de Paris, hasCutoffTime, time limit for completion]
-
A.
hasDeadline
Indicates that an entity is associated with a specific due date or time by which it must be completed or fulfilled.
-
B.
hasTimeStart
Indicates that an event, process, or state begins at a specific point in time.
-
C.
hasAllocatedTime
Indicates that a specific amount or period of time has been reserved or assigned for a particular entity, task, or activity.
-
D.
hasOfficialDuration
Indicates the formally defined length of time associated with an event, process, or entity.
-
E.
hasAwardPeriod
Indicates the time span or date range during which an award is valid, active, or applicable.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2d4b848190bf63fb3ed5d3b2d9 |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc133ef50819094c2b971f31f1615 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 8, 2026, 3:35 p.m.