Triple
T20758200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shatz |
E510901
|
entity |
| Predicate | hasMeaningExtension |
P141387
|
FINISHED |
| Object | darling |
—
|
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: darling | Statement: [Shatz, hasMeaningExtension, darling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningExtension Context triple: [Shatz, hasMeaningExtension, darling]
-
A.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
B.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
-
C.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
D.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
E.
hasPrefixMeaning
Indicates that one entity serves as a semantic prefix of another, contributing a specific meaning to the start of the second entity.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2464fb08190b6b141ca12d9f3f4 |
completed | April 21, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69e5c0509608819080cdbf47fcddfe36 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:35 p.m.