Triple
T21812294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carroll Barber |
E538505
|
entity |
| Predicate | storyThemes |
P73134
|
FINISHED |
| Object | love |
—
|
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: love | Statement: [Carroll Barber, storyThemes, love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyThemes Context triple: [Carroll Barber, storyThemes, love]
-
A.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
B.
fictionalTheme
Indicates that a work, element, or context is centered around or characterized by a fictional theme or motif.
-
C.
narrativeMotif
Indicates a recurring thematic element, pattern, or situation that appears across one or more narratives and helps structure or convey their underlying meanings.
-
D.
thematicCharacter
Indicates that an entity serves as a central or recurring figure embodying key themes or motifs within a narrative or discourse.
-
E.
dramaticTheme
chosen
Indicates that a work, scene, or narrative centers around a particular dramatic subject, motif, or emotional conflict as its main thematic focus.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc7ec1c8190a5420b44a49ae32f |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:53 p.m.