Triple
T16843773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dead Like You |
E409480
|
entity |
| Predicate | followsCaseType |
P81213
|
FINISHED |
| Object | serial rapist investigation |
—
|
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: serial rapist investigation | Statement: [Dead Like You, followsCaseType, serial rapist investigation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsCaseType Context triple: [Dead Like You, followsCaseType, serial rapist investigation]
-
A.
followsPlanType
Indicates that one entity adheres to, or is carried out according to, a specified type of plan.
-
B.
followUpType
Indicates the specific category or nature of a follow-up action or interaction that occurs after an initial event or communication.
-
C.
subsequentCase
Indicates that one legal case follows another in time or procedural order, often relying on or referencing the earlier case.
-
D.
caseTypes
chosen
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
E.
followsCharacterType
Indicates that one character’s behavior, role, or traits are patterned after, derived from, or constrained by a specified character type.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b35284588190a1d6238438f3e70d |
completed | April 18, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.