Triple
T33287070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becca Gilroy |
E852207
|
entity |
| Predicate | pregnancyStatusInPilot |
P41127
|
FINISHED |
| Object | pregnant |
—
|
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: pregnant | Statement: [Becca Gilroy, pregnancyStatusInPilot, pregnant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pregnancyStatusInPilot Context triple: [Becca Gilroy, pregnancyStatusInPilot, pregnant]
-
A.
weddingStatusInPilot
Indicates the marital or wedding-related status of entities specifically within the context of a pilot episode or initial trial scenario.
-
B.
hasPilotStatus
Indicates that an entity holds or is assigned a specific pilot-related status or role.
-
C.
hasStageOfPregnancy
Indicates that an entity is in, or associated with, a specific stage or phase of pregnancy.
-
D.
isPregnantIn
chosen
Indicates that an entity is in a state of pregnancy during a specified time or within a particular context.
-
E.
pregnantBy
Indicates that one entity is carrying a pregnancy that was biologically conceived by another specified 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_69f349660ff48190a4568803d0b89941 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:32 a.m.