Triple
T5585153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dark Eyes of London |
E146736
|
entity |
| Predicate | hasHorrorElements |
P64901
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [The Dark Eyes of London, hasHorrorElements, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHorrorElements Context triple: [The Dark Eyes of London, hasHorrorElements, yes]
-
A.
hasDramaticElements
Indicates that something contains features or qualities characteristic of drama, such as heightened emotion, tension, or conflict.
-
B.
containsSupernaturalElement
Indicates that the subject involves or features a supernatural, magical, or otherworldly element beyond normal natural laws.
-
C.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
D.
hasVillain
Indicates that one entity is the villain or primary antagonist associated with another entity.
-
E.
hasVampireCharacter
Indicates that an entity includes or features at least one character who is a vampire.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c02085d0e48190b8d185fe7f3d8579 |
completed | March 22, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:38 p.m.