Triple
T20663031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellie Cavanaugh |
E507805
|
entity |
| Predicate | ageDuringMainInvestigation |
P45004
|
FINISHED |
| Object | adult |
—
|
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: adult | Statement: [Ellie Cavanaugh, ageDuringMainInvestigation, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageDuringMainInvestigation Context triple: [Ellie Cavanaugh, ageDuringMainInvestigation, adult]
-
A.
ageAtTimeOfAccusation
Indicates the age a person was at the specific time when an accusation was made against them.
-
B.
ageStatus
chosen
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
C.
ageDuringMainEvents
Indicates the age an entity has at the time when the main events of a referenced context or narrative occur.
-
D.
ageAtIntroduction
Indicates the age an entity had at the time it was first introduced or presented in a given context.
-
E.
ageAtDisappearance
Indicates the age an individual was when they disappeared.
- 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f4872481908858eb88ce89dd47 |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.