Triple
T34368896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Lindsay Hiddingh |
E882097
|
entity |
| Predicate | familyTragedyInvolvedChildren |
P190083
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mary Lindsay Hiddingh, familyTragedyInvolvedChildren, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: familyTragedyInvolvedChildren Context triple: [Mary Lindsay Hiddingh, familyTragedyInvolvedChildren, true]
-
A.
numberOfChildVictims
Indicates the count of individuals who are victims and are classified as children in the context of the described event or situation.
-
B.
victimOfInjusticeInFamily
Indicates that one entity has suffered unfair or wrongful treatment within the context of their family relationships or family environment.
-
C.
familyLossEvent
Indicates an event in which a person experiences the loss or death of a family member.
-
D.
numberOfChildrenMurdered
Indicates the count of children who have been killed in an act of murder.
-
E.
childrenKilledBy
Indicates that the children of a given entity were killed by another specified entity or agent.
- 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_69f349be5c9c81908dc726ae1f4c68f2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69fcab6d41a88190a3576b4b088dcabd |
completed | May 7, 2026, 3:10 p.m. |
Created at: May 1, 2026, 1:58 a.m.