Triple
T38667451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murrays |
E940490
|
entity |
| Predicate | hasWordClass |
P198874
|
FINISHED |
| Object | properNounPlural |
—
|
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: properNounPlural | Statement: [Murrays, hasWordClass, properNounPlural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWordClass Context triple: [Murrays, hasWordClass, properNounPlural]
-
A.
morphologicalClass
Indicates the classification of an entity based on its morphological form or structural pattern.
-
B.
hasVerbClass
Indicates that an action or event is categorized into a specific verb class based on its grammatical or semantic behavior.
-
C.
hasNounClassCount
Indicates the number of distinct noun classes that are associated with or defined for a given entity.
-
D.
hasPartOfSpeechPattern
Indicates that something (such as a phrase, sentence, or expression) follows or exhibits a specific pattern of parts of speech.
-
E.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff0e9c75208190a4423261f00b79b3 |
completed | May 9, 2026, 10:38 a.m. |
| PD | Predicate disambiguation | batch_69ff0e07f08481909c4ae322632a6bf0 |
completed | May 9, 2026, 10:35 a.m. |
| PDg | Predicate description generation | batch_69ff0e9b7acc81909a0ee66201a06877 |
completed | May 9, 2026, 10:38 a.m. |
Created at: May 3, 2026, 4:33 p.m.