Triple
T34660980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miriam |
E890104
|
entity |
| Predicate | hasMeaningCandidate |
P199042
|
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: [Miriam, hasMeaningCandidate, “beloved”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningCandidate Context triple: [Miriam, hasMeaningCandidate, “beloved”]
-
A.
hasMeaningViaPatrick
Indicates that something possesses or conveys its meaning specifically through Patrick as the interpretive or mediating agent.
-
B.
hasFullyKnownMeaning
Indicates that the meaning of one entity is completely and unambiguously understood or specified in relation to another.
-
C.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
-
D.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
E.
hasMeaningExtension
Indicates that one entity represents an extended, elaborated, or more detailed meaning of another entity’s meaning.
- 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_69f349d906bc8190b2efd9eff237d94b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1c91bbac8190b84012dee1cb3b2c |
completed | May 9, 2026, 11:37 a.m. |
| PD | Predicate disambiguation | batch_69ff1c23ca508190bb5a435d765b7e53 |
completed | May 9, 2026, 11:36 a.m. |
| PDg | Predicate description generation | batch_69ff1c90c0f48190a3ede7b36ec77cfd |
completed | May 9, 2026, 11:37 a.m. |
Created at: May 1, 2026, 2:04 a.m.