Triple
T23895462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judith Harper |
E600890
|
entity |
| Predicate | hasRecurringStatus |
P90709
|
FINISHED |
| Object | recurring character |
—
|
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: recurring character | Statement: [Judith Harper, hasRecurringStatus, recurring character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringStatus Context triple: [Judith Harper, hasRecurringStatus, recurring character]
-
A.
recurringStatus
Indicates that an event, action, or state occurs repeatedly over time according to a defined recurrence pattern or schedule.
-
B.
hasRecurringElement
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
C.
hasRecurringRole
chosen
Indicates that an entity repeatedly appears or participates in a role within an ongoing or multiple related contexts over time.
-
D.
hasRecurringActor
Indicates that an actor appears repeatedly across multiple instances or episodes within a work or series.
-
E.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
- 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdd9203081909b10820a81c5d9d3 |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.