Triple
T29182874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Death (Castlevania) |
E739788
|
entity |
| Predicate | oftenEncounteredIn |
P177012
|
FINISHED |
| Object | Dracula's Castle |
—
|
NE NERFINISHED |
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: Dracula's Castle | Statement: [Death (Castlevania), oftenEncounteredIn, Dracula's Castle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenEncounteredIn Context triple: [Death (Castlevania), oftenEncounteredIn, Dracula's Castle]
-
A.
frequentlySeen
chosen
Indicates that one entity is observed or encountered many times or on a regular basis in relation to another entity.
-
B.
moreCommonIn
Indicates that something occurs with greater frequency or prevalence in one group, context, or location than in another.
-
C.
oftenSoughtOn
Indicates that one entity is frequently searched for, requested, or pursued in relation to another entity.
-
D.
oftenHave
Indicates that one entity frequently possesses, experiences, or is associated with another entity.
-
E.
encountered
Indicates that one entity came across or met another entity, typically in a specific place or context, often unexpectedly or during the course of some activity.
- 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 28, 2026, 11:58 a.m.