Triple
T3764715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mama Elena |
E82641
|
entity |
| Predicate | imposesRuleOn |
P8188
|
FINISHED |
| Object | Tita must care for her mother instead of marrying |
—
|
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: Tita must care for her mother instead of marrying | Statement: [Mama Elena, imposesRuleOn, Tita must care for her mother instead of marrying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imposesRuleOn Context triple: [Mama Elena, imposesRuleOn, Tita must care for her mother instead of marrying]
-
A.
setsRulesFor
chosen
Indicates that one entity establishes or defines rules, guidelines, or constraints that another entity is expected to follow.
-
B.
usesRulesFrom
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another entity.
-
C.
imposes
Indicates that one entity enforces, applies, or places a rule, condition, burden, or obligation upon another entity.
-
D.
imposedOn
Indicates that one party enforces, applies, or places a requirement, burden, or constraint onto another party or entity.
-
E.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbfd4be481908242c460a3f00c56 |
completed | March 8, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69adc04c851c8190ae5eaebf36df539b |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:35 p.m.