Triple
T9358603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Heidegger’s Experiment |
E225214
|
entity |
| Predicate | hasMacabreElements |
P64901
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dr. Heidegger’s Experiment, hasMacabreElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMacabreElements Context triple: [Dr. Heidegger’s Experiment, hasMacabreElements, true]
-
A.
hasHorrorElements
chosen
Indicates that something contains features, themes, or stylistic aspects characteristic of the horror genre.
-
B.
containsSupernaturalElement
Indicates that the subject involves or features a supernatural, magical, or otherworldly element beyond normal natural laws.
-
C.
hasDramaticElements
Indicates that something contains features or qualities characteristic of drama, such as heightened emotion, tension, or conflict.
-
D.
hasFictionalSubstance
Indicates that one entity includes, contains, or involves a fictional or imaginary substance as part of its composition, setting, or narrative.
-
E.
hasGraveGoods
Indicates that a burial or grave contains associated objects or goods placed with the deceased.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4ff19ab48190a8d85c8ac2644c89 |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.