Triple
T17939545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akhand Path |
E448550
|
entity |
| Predicate | readingPattern |
P37920
|
FINISHED |
| Object | continuous day-and-night recitation |
—
|
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: continuous day-and-night recitation | Statement: [Akhand Path, readingPattern, continuous day-and-night recitation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: readingPattern Context triple: [Akhand Path, readingPattern, continuous day-and-night recitation]
-
A.
readBehavior
Indicates that one entity engages in the act or manner of reading something, capturing how that reading is performed or characterized.
-
B.
readsTo
Indicates that one entity reads or recites content aloud for the benefit of another entity.
-
C.
readingApproach
chosen
Indicates the method, strategy, or manner in which an entity engages in reading a text.
-
D.
readingFeature
Indicates that an entity possesses a characteristic, capability, or attribute specifically related to reading.
-
E.
readBy
Indicates that a particular text, document, or content item has been read or consumed by a specific person or agent.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad9533688190bff773c183ed8505 |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8e713d481908b4a126258c18b63 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.