Triple
T23527220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yossi |
E576464
|
entity |
| Predicate | hasMeaningViaYosef |
P153108
|
FINISHED |
| Object | “He will add” |
—
|
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: “He will add” | Statement: [Yossi, hasMeaningViaYosef, “He will add”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningViaYosef Context triple: [Yossi, hasMeaningViaYosef, “He will add”]
-
A.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
B.
hebrewMeaning
Indicates that one entity specifies or provides the meaning or translation of another entity in the Hebrew language.
-
C.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
-
D.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
E.
hasMeaningInChinese
Indicates that one entity (such as a word, phrase, or symbol) possesses a specific meaning or interpretation within the Chinese 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac74be1881909161b94aa611188a |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f12760784c8190aaeff002ef31febe |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 17, 2026, 6:09 p.m.