Triple
T19619918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ambika |
E470974
|
entity |
| Predicate | reasonForBlindSon |
P6484
|
FINISHED |
| Object | closed her eyes during union with 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: closed her eyes during union with Vyasa | Statement: [Ambika, reasonForBlindSon, closed her eyes during union with Vyasa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForBlindSon Context triple: [Ambika, reasonForBlindSon, closed her eyes during union with Vyasa]
-
A.
reasonForBlindfold
Indicates that the predicate specifies the cause or purpose for which an entity is blindfolded.
-
B.
blindedBy
Indicates that one entity causes another to lose the ability to see or perceive clearly, either literally or metaphorically.
-
C.
blinded
Indicates that one entity causes another to lose the ability to see, either temporarily or permanently.
-
D.
refusedToExplain
Indicates that an entity declined or failed to provide an explanation about something to another entity or audience.
-
E.
originalReason
chosen
Indicates the initial cause, motivation, or justification behind an action, decision, or state of affairs.
- 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e512d08190a76bf81b3282e0e5 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.