Triple
T19983940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troubled Blood |
E493886
|
entity |
| Predicate | centralCaseType |
P81213
|
FINISHED |
| Object | cold case |
—
|
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: cold case | Statement: [Troubled Blood, centralCaseType, cold case]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: centralCaseType Context triple: [Troubled Blood, centralCaseType, cold case]
-
A.
centralToCase
Indicates that something plays a pivotal or essential role in determining the outcome or understanding of a particular case.
-
B.
caseTypes
chosen
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
C.
primaryCase
Indicates that an entity is the main or leading instance in a set of related cases or occurrences.
-
D.
centralAppeal
Indicates that something serves as the main attraction, focus, or compelling feature that draws interest or attention.
-
E.
centerType
Indicates the classification or category of a center (e.g., type of facility, institution, or hub) associated with an entity.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d157d088190af861608936e59b7 |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:28 p.m.