Triple
T17517735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tranquility |
E426607
|
entity |
| Predicate | hasDowntime |
P71131
|
FINISHED |
| Object | daily scheduled maintenance |
—
|
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: daily scheduled maintenance | Statement: [Tranquility, hasDowntime, daily scheduled maintenance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDowntime Context triple: [Tranquility, hasDowntime, daily scheduled maintenance]
-
A.
hasBlackouts
Indicates that an entity experiences periods of complete or partial loss of consciousness, awareness, or memory.
-
B.
hasMaintenance
chosen
Indicates that an entity is subject to, associated with, or requires a particular maintenance activity or maintenance record.
-
C.
hasServiceTime
Indicates that an entity is associated with a specific duration or schedule during which a service is provided.
-
D.
hasDays
Indicates that an entity is associated with, spans, or occurs on specific days.
-
E.
isBusyDuring
Indicates that an entity is occupied or engaged with some activity throughout a specified time period.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452615a8481909974e9855ea7a8e4 |
completed | April 19, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:49 a.m.