Triple
T32402061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banalata Sen (poetry collection) |
E827977
|
entity |
| Predicate | hasRecurringImage |
P10543
|
FINISHED |
| Object | wandering traveler |
—
|
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: wandering traveler | Statement: [Banalata Sen (poetry collection), hasRecurringImage, wandering traveler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringImage Context triple: [Banalata Sen (poetry collection), hasRecurringImage, wandering traveler]
-
A.
hasRecurringElement
chosen
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
B.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
C.
hasRecurringSpecial
Indicates that an entity regularly offers or features a special deal, item, or promotion that recurs over time.
-
D.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
-
E.
hasImagingCadence
Indicates the regular interval or frequency at which imaging observations are repeatedly acquired.
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a0227ce59a081909fe1ba1181d86b4d |
completed | May 11, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_6a02273989208190beb948b8c7bdaee3 |
completed | May 11, 2026, 7 p.m. |
Created at: May 1, 2026, 12:52 a.m.