Triple
T38625883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bièvre river (covered section) |
E937005
|
entity |
| Predicate | reasonForCovering |
P24667
|
FINISHED |
| Object | sanitation concerns |
—
|
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: sanitation concerns | Statement: [Bièvre river (covered section), reasonForCovering, sanitation concerns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForCovering Context triple: [Bièvre river (covered section), reasonForCovering, sanitation concerns]
-
A.
mayCover
Indicates that one entity is permitted or able to extend over, include, or provide coverage for another entity, either partially or fully.
-
B.
coverUpBy
Indicates that one entity conceals, suppresses, or hides the actions, information, or wrongdoing associated with another entity.
-
C.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
-
D.
usedCover
Indicates that one entity employed another entity as a protective or concealing cover in a given context.
-
E.
protectionReason
chosen
Indicates the justification or cause for which protection is provided or required in the relationship between entities.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe7eb4b8348190bb19d35766189ed4 |
completed | May 9, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69fe7c35d2148190ab952e54feda1e76 |
completed | May 9, 2026, 12:13 a.m. |
Created at: May 3, 2026, 4:32 p.m.