Triple
T10935545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monarch |
E258321
|
entity |
| Predicate | relationshipWithTitans |
P96720
|
FINISHED |
| Object | stewardship |
—
|
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: stewardship | Statement: [Monarch, relationshipWithTitans, stewardship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithTitans Context triple: [Monarch, relationshipWithTitans, stewardship]
-
A.
relationshipToVigilantes
Indicates the nature or type of connection an entity has with vigilantes, such as affiliation, opposition, support, or other relational stance.
-
B.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
C.
relationshipToCharacter
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
D.
associatedBeings
Indicates that two or more beings are linked or connected to each other in some relevant way.
-
E.
relationshipToTopa
Indicates a familial or social relationship that an entity has specifically with Topa.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770aee178819082c1671a37ff7d82 |
completed | April 9, 2026, 9:26 a.m. |
| PD | Predicate disambiguation | batch_69d72e816a98819096d6c10dfb88a66a |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.