Triple
T23486796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Howland |
E570554
|
entity |
| Predicate | marriageStartWithCharlesKimbrough |
P152563
|
FINISHED |
| Object | 2002 |
—
|
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: 2002 | Statement: [Beth Howland, marriageStartWithCharlesKimbrough, 2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageStartWithCharlesKimbrough Context triple: [Beth Howland, marriageStartWithCharlesKimbrough, 2002]
-
A.
marriageStartTimeWithCharlieBrooks
Indicates the time at which a marriage involving Charlie Brooks began.
-
B.
marriageStartWithCaitlinMcHugh
Indicates the point in time when an individual begins a marital relationship with Caitlin McHugh.
-
C.
marriageStartWithCatherineBrelet
Indicates the point in time when an entity begins a marital relationship with Catherine Brelet.
-
D.
marriageStartDateWithRobertCarr
Indicates the date on which an entity’s marriage to Robert Carr began.
-
E.
startTimeOfMarriageToLauraCharteris
Indicates the specific date and time when an individual’s marriage to Laura Charteris began.
- F. None of above. chosen
Provenance (4 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a754825481909b005ca5654c3159 |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:04 p.m.