Triple
T4680435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grotte de l’Aven Noir |
E103784
|
entity |
| Predicate | hasSafetyEquipment |
P26738
|
FINISHED |
| Object | fixed ropes |
—
|
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: fixed ropes | Statement: [Grotte de l’Aven Noir, hasSafetyEquipment, fixed ropes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyEquipment Context triple: [Grotte de l’Aven Noir, hasSafetyEquipment, fixed ropes]
-
A.
safetyEquipment
chosen
Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
-
B.
protectiveEquipment
Indicates that one entity serves as protective equipment used to safeguard another entity from harm or risk.
-
C.
hasSafetyInfrastructure
Indicates that appropriate safety-related structures, systems, or measures are present for the referenced entity or environment.
-
D.
hasSafetyCertificate
Indicates that an entity possesses or has been granted a valid safety certificate.
-
E.
measuresSafetyUsing
Indicates that an entity evaluates or assesses safety by employing a specified method, tool, or standard.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6217e0088190836570522e324dc6 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:16 p.m.