Triple
T4523746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dhritarashtra |
E103326
|
entity |
| Predicate | causeOfBlindness |
P22656
|
FINISHED |
| Object | born blind due to Ambika’s fear of Vyasa |
—
|
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: born blind due to Ambika’s fear of Vyasa | Statement: [Dhritarashtra, causeOfBlindness, born blind due to Ambika’s fear of Vyasa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfBlindness Context triple: [Dhritarashtra, causeOfBlindness, born blind due to Ambika’s fear of Vyasa]
-
A.
coma
Indicates that an entity is in a state of prolonged unconsciousness and unresponsiveness, typically due to severe injury or illness.
-
B.
eyeCondition
Indicates that an entity has, experiences, or is characterized by a particular condition or disorder affecting the eyes.
-
C.
causeOfDisability
Indicates that one entity is the reason or source that brings about another entity’s disability.
-
D.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
E.
blindedBy
chosen
Indicates that one entity causes another to lose the ability to see or perceive clearly, either literally or metaphorically.
- 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_69bd43dba59881908cf59b31df8c7ae1 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd574d7c2481909049955ca47613a6 |
completed | March 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69bd521cf77c819083852de3094d1377 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:03 p.m.