Triple
T33457451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ابن جني |
E856815
|
entity |
| Predicate | موضوع كتاب الخصائص |
P157125
|
FINISHED |
| Object | أصول النحو وفلسفة اللغة |
—
|
NE NERFINISHED |
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: أصول النحو وفلسفة اللغة | Statement: [ابن جني, موضوع كتاب الخصائص, أصول النحو وفلسفة اللغة]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: موضوع كتاب الخصائص Context triple: [ابن جني, موضوع كتاب الخصائص, أصول النحو وفلسفة اللغة]
-
A.
bookCharacteristic
chosen
Indicates that a particular characteristic, feature, or attribute is associated with a given book.
-
B.
libraryCharacteristic
Indicates that a specified characteristic, feature, or property is associated with a particular library.
-
C.
وصفه
Indicates that one entity describes, characterizes, or portrays another entity.
-
D.
عدد الحروف
Indicates the relationship that specifies the number of letters contained in a given word or text.
-
E.
מאפיין מסורתי
Indicates a traditional characteristic or attribute that is typically associated with something based on long-standing customs or heritage.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e4cff8c08190aecaabf722cf3891 |
completed | May 3, 2026, 6:01 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
Created at: May 1, 2026, 1:37 a.m.