Triple
T8666600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bayta Darell |
E205689
|
entity |
| Predicate | seriesOrderOfFirstAppearance |
P83971
|
FINISHED |
| Object | second book of the Foundation series |
—
|
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: second book of the Foundation series | Statement: [Bayta Darell, seriesOrderOfFirstAppearance, second book of the Foundation series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesOrderOfFirstAppearance Context triple: [Bayta Darell, seriesOrderOfFirstAppearance, second book of the Foundation series]
-
A.
seriesDebut
Indicates the first appearance or initial release of a series in which the subject entity is introduced.
-
B.
characterFirstAppearanceInThisPortrayal
Indicates that this is the first time the character appears in the specific portrayal or adaptation being referenced.
-
C.
settingOfFirstAppearance
Indicates the location or context in which an entity is first introduced or appears.
-
D.
firstAppearanceFranchise
Indicates the franchise in which an entity made its first appearance.
-
E.
firstAppearanceInComicsIssue
Indicates the specific comic book issue in which an entity (such as a character or item) is depicted for the first time.
- F. None of above. chosen
Provenance (4 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a1dd1481908c56abca48fcd562 |
completed | March 31, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:31 p.m.