Triple
T4836163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Draupadi |
E108063
|
entity |
| Predicate | husbandOrderRule |
P4764
|
FINISHED |
| Object | each Pandava to spend a year with her in turn |
—
|
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: each Pandava to spend a year with her in turn | Statement: [Draupadi, husbandOrderRule, each Pandava to spend a year with her in turn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: husbandOrderRule Context triple: [Draupadi, husbandOrderRule, each Pandava to spend a year with her in turn]
-
A.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
B.
marriedToRank
Indicates that one entity is married to another entity who holds a specific rank or position.
-
C.
choseAsHusband
Indicates that one entity selected another entity to be her husband, typically as a marital partner.
-
D.
governedThroughSpouse
Indicates that one entity exercised governing authority or political power indirectly through their spouse, who held the formal ruling position.
-
E.
orderOf
Indicates that one entity is arranged, ranked, or sequenced before or after another according to a specified ordering criterion.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c21c7f08190846049d31fdfa144 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.