Triple
T37285722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Beggar Maid |
E925527
|
entity |
| Predicate | relationshipToKingCophetua |
P205818
|
FINISHED |
| Object | beloved |
—
|
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: beloved | Statement: [the Beggar Maid, relationshipToKingCophetua, beloved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToKingCophetua Context triple: [the Beggar Maid, relationshipToKingCophetua, beloved]
-
A.
relationshipToKingShahryar
Indicates the type or nature of a person's relationship to King Shahryar, such as familial, marital, or social connection.
-
B.
relationshipToHarpagon
Indicates the specific familial or social relationship that an entity has to the character Harpagon.
-
C.
relationshipToPrincess
Indicates the specific familial, social, or romantic connection that one entity has to a princess.
-
D.
relationshipToQueenOfHearts
Indicates the specific familial, social, or hierarchical relationship that one entity has to the Queen of Hearts.
-
E.
relationToAndrewMartin
Indicates a relationship that specifies how one entity is connected or related to Andrew Martin.
- 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_69f76eafe20c8190856d3b996a4c31a7 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:16 p.m.