Triple
T26499934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biswambhar Roy |
E669389
|
entity |
| Predicate | personalTragedy |
P41242
|
FINISHED |
| Object | financial ruin |
—
|
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: financial ruin | Statement: [Biswambhar Roy, personalTragedy, financial ruin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personalTragedy Context triple: [Biswambhar Roy, personalTragedy, financial ruin]
-
A.
familyLossEvent
Indicates an event in which a person experiences the loss or death of a family member.
-
B.
trauma
chosen
Indicates that an entity has experienced a deeply distressing or harmful event or series of events that cause lasting psychological or emotional impact.
-
C.
otherMajorTragedy
Indicates that the subject experienced or was involved in a significant tragic event other than the primary or most notable tragedy under consideration.
-
D.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
E.
mourningCause
Indicates that one entity is in a state of mourning specifically because of the other entity, which is the cause or reason for the grief.
- 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_69eeb319007081909642b414b114b35a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6247480cc8190a887eedaeb94615c |
completed | May 2, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69f623a7539c8190b71797f583da9f63 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 1:12 a.m.