Triple
T467694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Long Dark Tea-Time of the Soul |
E8484
|
entity |
| Predicate | hasProtagonistOccupation |
P2374
|
FINISHED |
| Object | holistic detective |
—
|
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: holistic detective | Statement: [The Long Dark Tea-Time of the Soul, hasProtagonistOccupation, holistic detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistOccupation Context triple: [The Long Dark Tea-Time of the Soul, hasProtagonistOccupation, holistic detective]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
portraysProfession
Indicates that one entity depicts or represents another entity in a specific profession or occupational role.
-
C.
mainProtagonist
Indicates that the subject is the central character or primary focus in the narrative of the related work.
-
D.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd9bea081909ee782840f3da12b |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edebb3988190907992a584b4e260 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.