Triple
T19594456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Ayodhya |
E470314
|
entity |
| Predicate | relationshipToRama |
P136400
|
FINISHED |
| Object | stepmother |
—
|
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: stepmother | Statement: [Queen of Ayodhya, relationshipToRama, stepmother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToRama Context triple: [Queen of Ayodhya, relationshipToRama, stepmother]
-
A.
relationshipToRa
Indicates a specified type of relational connection that an entity has to the entity Ra.
-
B.
relationshipToTopa
Indicates a familial or social relationship that an entity has specifically with Topa.
-
C.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
D.
relationshipToMahāpajāpatīGotamī
Indicates the specific familial or relational connection an entity has to Mahāpajāpatī Gotamī.
-
E.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640793cd88190b9b84491bfb2493f |
completed | April 20, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69e514dbdb988190b55931a8138c73e7 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e5174b060c81908937ff9ff7fce611 |
completed | April 19, 2026, 5:56 p.m. |
Created at: April 10, 2026, 1:43 p.m.