Triple
T11674227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ānanda |
E277450
|
entity |
| Predicate | associatedTextFormula |
P8272
|
FINISHED |
| Object | “Evaṃ me sutaṃ” |
—
|
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: “Evaṃ me sutaṃ” | Statement: [Ānanda, associatedTextFormula, “Evaṃ me sutaṃ”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedTextFormula Context triple: [Ānanda, associatedTextFormula, “Evaṃ me sutaṃ”]
-
A.
associatedWithText
chosen
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
B.
relatedByFormula
Indicates that one entity is mathematically or logically derived from, or connected to, another according to a specific formula.
-
C.
formulaUsed
Indicates that a particular formula is employed or applied in performing a calculation, derivation, or reasoning step.
-
D.
formulaType
Indicates the specific kind or category of formula associated with an entity or expression.
-
E.
primaryFormulaFormat
Indicates the main or default structural format in which a formula is represented or stored.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a443b6848190a1eb6825fbc49d08 |
completed | April 10, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69d88a77e6e88190b7519100bde76575 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:40 p.m.